HayStack_Tutorial15_TableQA+TextQA.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DeAkZwDhufYA"
      },
      "source": [
        "# Open-Domain QA on Tables\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial15_TableQA.ipynb)\n",
        "\n",
        "This tutorial shows you how to perform question-answering on tables using the `TableTextRetriever` or `ElasticsearchRetriever` as retriever node and the `TableReader` as reader node."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vbR3bETlvi-3"
      },
      "source": [
        "### Prepare environment\n",
        "\n",
        "#### Colab: Enable the GPU runtime\n",
        "Make sure you enable the GPU runtime to experience decent speed in this tutorial.\n",
        "**Runtime -> Change Runtime type -> Hardware accelerator -> GPU**\n",
        "\n",
        "<img src=\"https://raw.githubusercontent.com/deepset-ai/haystack/master/docs/img/colab_gpu_runtime.jpg\">"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "HW66x0rfujyO",
        "outputId": "30b45cfc-76df-41f6-abe5-dde63aa2b899",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mon Apr 18 23:48:39 2022       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla K80           Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   69C    P8    31W / 149W |      0MiB / 11441MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "# Make sure you have a GPU running\n",
        "!nvidia-smi"
      ]
    },
    {
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      "execution_count": 2,
      "metadata": {
        "id": "_ZXoyhOAvn7M",
        "outputId": "b4cfe550-7bd1-439a-e2d5-e325b10ed179",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
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            "Building wheels for collected packages: sentence-transformers, farm-haystack, langdetect, python-docx, seqeval, tika, alembic, databricks-cli\n",
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            "  Created wheel for tika: filename=tika-1.24-py3-none-any.whl size=32893 sha256=8890dc59131ce6367a2353bdb6ddfea6289ff13bd78c9d9b4d194548ddd382ef\n",
            "  Stored in directory: /root/.cache/pip/wheels/ec/2b/38/58ff05467a742e32f67f5d0de048fa046e764e2fbb25ac93f3\n",
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            "  Created wheel for alembic: filename=alembic-1.4.1-py2.py3-none-any.whl size=158171 sha256=1b56279d018a2c35061f20aee26a8e7d22f6e5a0b7fa580e48ac59584acad192\n",
            "  Stored in directory: /root/.cache/pip/wheels/be/5d/0a/9e13f53f4f5dfb67cd8d245bb7cdffe12f135846f491a283e3\n",
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            "  Created wheel for databricks-cli: filename=databricks_cli-0.16.6-py3-none-any.whl size=112631 sha256=ac8283f55b792ca3a6db39d1d1946c6603dec55fc5fe95040b8d12278e81699a\n",
            "  Stored in directory: /root/.cache/pip/wheels/96/c1/f8/d75a22e789ab6a4dff11f18338c3af4360189aa371295cc934\n",
            "Successfully built sentence-transformers farm-haystack langdetect python-docx seqeval tika alembic databricks-cli\n",
            "Installing collected packages: tokenizers, sentencepiece, python-editor, monotonic, mmh3, azure-common, websocket-client, smmap, sacremoses, querystring-parser, pyyaml, python-docx, pyjwt, pydantic, num2words, langdetect, jarowinkler, isodate, gunicorn, grpcio, elasticsearch, elastic-apm, backoff, tika, rapidfuzz, quantulum3, posthog, Mako, huggingface-hub, gitdb, docker, databricks-cli, cryptography, azure-core, transformers, seqeval, prometheus-flask-exporter, msrest, gitpython, alembic, sentence-transformers, azure-storage-blob, azure-ai-formrecognizer, mlflow, farm-haystack\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "  Attempting uninstall: grpcio\n",
            "    Found existing installation: grpcio 1.44.0\n",
            "    Uninstalling grpcio-1.44.0:\n",
            "      Successfully uninstalled grpcio-1.44.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tensorflow 2.8.0 requires tf-estimator-nightly==2.8.0.dev2021122109, which is not installed.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed Mako-1.2.0 alembic-1.4.1 azure-ai-formrecognizer-3.2.0b2 azure-common-1.1.28 azure-core-1.22.1 azure-storage-blob-12.11.0 backoff-1.11.1 cryptography-36.0.2 databricks-cli-0.16.6 docker-5.0.3 elastic-apm-6.9.1 elasticsearch-7.10.0 farm-haystack-1.3.1rc0 gitdb-4.0.9 gitpython-3.1.27 grpcio-1.43.0 gunicorn-20.1.0 huggingface-hub-0.5.1 isodate-0.6.1 jarowinkler-1.0.2 langdetect-1.0.9 mlflow-1.13.1 mmh3-3.0.0 monotonic-1.6 msrest-0.6.21 num2words-0.5.10 posthog-1.4.6 prometheus-flask-exporter-0.20.1 pydantic-1.9.0 pyjwt-2.3.0 python-docx-0.8.11 python-editor-1.0.4 pyyaml-6.0 quantulum3-0.7.10 querystring-parser-1.2.4 rapidfuzz-2.0.10 sacremoses-0.0.49 sentence-transformers-2.2.0 sentencepiece-0.1.96 seqeval-1.2.2 smmap-5.0.0 tika-1.24 tokenizers-0.10.3 transformers-4.13.0 websocket-client-1.3.2\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0mLooking in links: https://data.pyg.org/whl/torch-1.10.0+cu113.html\n",
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            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "# Install the latest release of Haystack in your own environment\n",
        "#! pip install farm-haystack\n",
        "\n",
        "# Install the latest master of Haystack\n",
        "!pip install --upgrade pip\n",
        "!pip install git+https://github.com/deepset-ai/haystack.git#egg=farm-haystack[colab]\n",
        "\n",
        "# The TaPAs-based TableReader requires the torch-scatter library\n",
        "!pip install torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+cu113.html\n",
        "\n",
        "# Install pygraphviz for visualization of Pipelines\n",
        "!apt install libgraphviz-dev\n",
        "!pip install pygraphviz"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K_XJhluXwF5_"
      },
      "source": [
        "### Start an Elasticsearch server\n",
        "You can start Elasticsearch on your local machine instance using Docker. If Docker is not readily available in your environment (e.g. in Colab notebooks), then you can manually download and execute Elasticsearch from source."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "frDqgzK7v2i1",
        "outputId": "32759892-ec3d-4595-95c3-ce3ac90f5050",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.optimization -  apex not found, won't use it. See https://nvidia.github.io/apex/\n",
            "WARNING - haystack.utils.doc_store -  Tried to start Elasticsearch through Docker but this failed. It is likely that there is already an existing Elasticsearch instance running. \n"
          ]
        }
      ],
      "source": [
        "# Recommended: Start Elasticsearch using Docker via the Haystack utility function\n",
        "from haystack.utils import launch_es\n",
        "\n",
        "launch_es()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "S4PGj1A6wKWu"
      },
      "outputs": [],
      "source": [
        "# In Colab / No Docker environments: Start Elasticsearch from source\n",
        "! wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.9.2-linux-x86_64.tar.gz -q\n",
        "! tar -xzf elasticsearch-7.9.2-linux-x86_64.tar.gz\n",
        "! chown -R daemon:daemon elasticsearch-7.9.2\n",
        "\n",
        "import os\n",
        "from subprocess import Popen, PIPE, STDOUT\n",
        "\n",
        "es_server = Popen(\n",
        "    [\"elasticsearch-7.9.2/bin/elasticsearch\"], stdout=PIPE, stderr=STDOUT, preexec_fn=lambda: os.setuid(1)  # as daemon\n",
        ")\n",
        "# wait until ES has started\n",
        "! sleep 30"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "RmxepXZtwQ0E",
        "outputId": "940ad995-46c5-4837-f5be-f325bca932f7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.telemetry -  Haystack sends anonymous usage data to understand the actual usage and steer dev efforts towards features that are most meaningful to users. You can opt-out at anytime by calling disable_telemetry() or by manually setting the environment variable HAYSTACK_TELEMETRY_ENABLED as described for different operating systems on the documentation page. More information at https://haystack.deepset.ai/guides/telemetry\n"
          ]
        }
      ],
      "source": [
        "# Connect to Elasticsearch\n",
        "from haystack.document_stores import ElasticsearchDocumentStore\n",
        "\n",
        "# We want to use a small model producing 512-dimensional embeddings, so we need to set embedding_dim to 512\n",
        "document_index = \"document\"\n",
        "document_store = ElasticsearchDocumentStore(\n",
        "    host=\"localhost\", username=\"\", password=\"\", index=document_index, embedding_dim=512\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fFh26LIlxldw"
      },
      "source": [
        "## Add Tables to DocumentStore\n",
        "To quickly demonstrate the capabilities of the `TableTextRetriever` and the `TableReader` we use a subset of 1000 tables and text documents from a dataset we have published in [this paper](https://arxiv.org/abs/2108.04049).\n",
        "\n",
        "Just as text passages, tables are represented as `Document` objects in Haystack. The content field, though, is a pandas DataFrame instead of a string."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "nM63uwbd8zd6",
        "outputId": "71a42718-99db-442e-96b7-1e285c999626",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.utils.import_utils -  Fetching from https://s3.eu-central-1.amazonaws.com/deepset.ai-farm-qa/datasets/documents/table_text_dataset.zip to `data/tutorial15`\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "# Let's first fetch some tables that we want to query\n",
        "# Here: 1000 tables from OTT-QA\n",
        "from haystack.utils import fetch_archive_from_http\n",
        "\n",
        "doc_dir = \"data/tutorial15\"\n",
        "s3_url = \"https://s3.eu-central-1.amazonaws.com/deepset.ai-farm-qa/datasets/documents/table_text_dataset.zip\"\n",
        "fetch_archive_from_http(url=s3_url, output_dir=doc_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SKjw2LuXxlGh",
        "outputId": "ab660d65-32ca-42c0-c093-397bb4d8a924"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                Opponent    M    W    L  T  NR   Win% First  Last\n",
            "0            Afghanistan    2    2    0  0   0  100.0  2012  2014\n",
            "1              Australia   98   32   62  1   3  34.21  1975  2017\n",
            "2             Bangladesh   35   31    4  0   0  88.57  1986  2015\n",
            "3                 Canada    2    2    0  0   0  100.0  1979  2011\n",
            "4                England   82   31   49  0   2  38.75  1974  2017\n",
            "5              Hong Kong    2    2    0  0   0  100.0  2004  2008\n",
            "6                  India  129   73   52  0   4   58.4  1978  2017\n",
            "7                Ireland    7    5    1  1   0  78.57  2007  2016\n",
            "8                  Kenya    6    6    0  0   0  100.0  1996  2011\n",
            "9                Namibia    1    1    0  0   0  100.0  2003  2003\n",
            "10           Netherlands    3    3    0  0   0  100.0  1996  2003\n",
            "11           New Zealand  103   53   47  1   2  52.97  1973  2018\n",
            "12              Scotland    3    3    0  0   0  100.0  1999  2013\n",
            "13          South Africa   73   25   47  0   1  34.72  1992  2017\n",
            "14             Sri Lanka  153   90   58  1   4  60.73  1975  2017\n",
            "15  United Arab Emirates    3    3    0  0   0  100.0  1994  2015\n",
            "16           West Indies  133   60   70  3   0  46.24  1975  2017\n",
            "17              Zimbabwe   59   52    4  1   2   92.1  1992  2018\n",
            "18             Total[12]  894  474  394  8  18  54.56  1973  2018\n",
            "{}\n"
          ]
        }
      ],
      "source": [
        "# Add the tables to the DocumentStore\n",
        "\n",
        "import json\n",
        "from haystack import Document\n",
        "import pandas as pd\n",
        "\n",
        "\n",
        "def read_tables(filename):\n",
        "    processed_tables = []\n",
        "    with open(filename) as tables:\n",
        "        tables = json.load(tables)\n",
        "        for key, table in tables.items():\n",
        "            current_columns = table[\"header\"]\n",
        "            current_rows = table[\"data\"]\n",
        "            current_df = pd.DataFrame(columns=current_columns, data=current_rows)\n",
        "            document = Document(content=current_df, content_type=\"table\", id=key)\n",
        "            processed_tables.append(document)\n",
        "\n",
        "    return processed_tables\n",
        "\n",
        "\n",
        "tables = read_tables(f\"{doc_dir}/tables.json\")\n",
        "document_store.write_documents(tables, index=document_index)\n",
        "\n",
        "# Showing content field and meta field of one of the Documents of content_type 'table'\n",
        "print(tables[0].content)\n",
        "print(tables[0].meta)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hmQC1sDmw3d7"
      },
      "source": [
        "## Initalize Retriever, Reader, & Pipeline\n",
        "\n",
        "### Retriever\n",
        "\n",
        "Retrievers help narrowing down the scope for the Reader to a subset of tables where a given question could be answered.\n",
        "They use some simple but fast algorithm.\n",
        "\n",
        "**Here:** We use the `TableTextRetriever` capable of retrieving relevant content among a database\n",
        "of texts and tables using dense embeddings. It is an extension of the `DensePassageRetriever` and consists of three encoders (one query encoder, one text passage encoder and one table encoder) that create embeddings in the same vector space. More details on the `TableTextRetriever` and how it is trained can be found in [this paper](https://arxiv.org/abs/2108.04049).\n",
        "\n",
        "**Alternatives:**\n",
        "\n",
        "- `ElasticsearchRetriever` that uses BM25 algorithm\n"
      ]
    },
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      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.utils -  Using devices: CUDA:0\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n"
          ]
        },
        {
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            "application/vnd.jupyter.widget-view+json": {
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            }
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              "model_id": "dff4230178df4d2db8089e26061cf817"
            }
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.language_model -  LOADING MODEL\n",
            "INFO - haystack.modeling.model.language_model -  =============\n",
            "INFO - haystack.modeling.model.language_model -  Could not find deepset/bert-small-mm_retrieval-question_encoder locally.\n",
            "INFO - haystack.modeling.model.language_model -  Looking on Transformers Model Hub (in local cache and online)...\n"
          ]
        },
        {
          "output_type": "display_data",
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "c04064c6ec984da59fd992cbd9d7b1f4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.language_model -  Loaded deepset/bert-small-mm_retrieval-question_encoder\n"
          ]
        },
        {
          "output_type": "display_data",
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              "model_id": "dbb76aeefb7a41b68f7bcb0ef2ae3f72"
            }
          },
          "metadata": {}
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            }
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            }
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          "metadata": {}
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f39a4d231f94414494e0340405fae66b"
            }
          },
          "metadata": {}
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "da0281d036904c6991868a2fdc5fde8b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'DPRQuestionEncoderTokenizer'. \n",
            "The class this function is called from is 'DPRContextEncoderTokenizerFast'.\n",
            "INFO - haystack.modeling.model.language_model -  LOADING MODEL\n",
            "INFO - haystack.modeling.model.language_model -  =============\n",
            "INFO - haystack.modeling.model.language_model -  Could not find deepset/bert-small-mm_retrieval-passage_encoder locally.\n",
            "INFO - haystack.modeling.model.language_model -  Looking on Transformers Model Hub (in local cache and online)...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2b00a1264326463d8b954ceb0c4df8d9"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.language_model -  Loaded deepset/bert-small-mm_retrieval-passage_encoder\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f4f753e4e7264795b8ec3319db9550b8"
            }
          },
          "metadata": {}
        },
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            "application/vnd.jupyter.widget-view+json": {
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              "model_id": "2d256aef6e66479181c18452115db13e"
            }
          },
          "metadata": {}
        },
        {
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            "application/vnd.jupyter.widget-view+json": {
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              "model_id": "b8bedd360626483582c130f5ef42c25d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ce4307bc6ae849959d613a00ddb3e0da"
            }
          },
          "metadata": {}
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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              "version_minor": 0,
              "model_id": "301b2b302ccf4a78a702b76902b6e7b4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'DPRQuestionEncoderTokenizer'. \n",
            "The class this function is called from is 'DPRContextEncoderTokenizerFast'.\n",
            "INFO - haystack.modeling.model.language_model -  LOADING MODEL\n",
            "INFO - haystack.modeling.model.language_model -  =============\n",
            "INFO - haystack.modeling.model.language_model -  Could not find deepset/bert-small-mm_retrieval-table_encoder locally.\n",
            "INFO - haystack.modeling.model.language_model -  Looking on Transformers Model Hub (in local cache and online)...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/110M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "81d0ad8b336140db8796c75aa610c7fc"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.language_model -  Loaded deepset/bert-small-mm_retrieval-table_encoder\n"
          ]
        }
      ],
      "source": [
        "from haystack.nodes.retriever import TableTextRetriever\n",
        "\n",
        "retriever = TableTextRetriever(\n",
        "    document_store=document_store,\n",
        "    query_embedding_model=\"deepset/bert-small-mm_retrieval-question_encoder\",\n",
        "    passage_embedding_model=\"deepset/bert-small-mm_retrieval-passage_encoder\",\n",
        "    table_embedding_model=\"deepset/bert-small-mm_retrieval-table_encoder\",\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "jasi1RM2zIJ7",
        "outputId": "fa29f0b9-3a9e-4c59-fceb-55a3a678575d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "1bebaa8e836646bf8210fce1f586bcab",
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            "114a7f98f13d4ea29fe4c73da9c8ab02",
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            "fe9caa820f194bc2a7933aff941712bb",
            "4f24bb96ae3c4ee6861c3640bb957e70",
            "0e4b510a474d4091a2665aabdfc7a5b6",
            "958535b27b964142b91ad8332d7ee513",
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            "c9f94bd9bc8543ec87034f55069ce626",
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            "889bf4198f394f7199defcbed713d963",
            "99831be96e464c1bbc8beae281b6462d"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.document_stores.elasticsearch -  Updating embeddings for all 437 docs ...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Updating embeddings:   0%|          | 0/437 [00:00<?, ? Docs/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1bebaa8e836646bf8210fce1f586bcab"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Create embeddings:   0%|          | 0/448 [00:00<?, ? Docs/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "528d7c9eaedd481f980aac8d30a653c4"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Add table embeddings to the tables in DocumentStore\n",
        "document_store.update_embeddings(retriever=retriever)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "XM-ijy6Zz11L"
      },
      "outputs": [],
      "source": [
        "## Alternative: ElasticsearchRetriever\n",
        "# from haystack.nodes.retriever import ElasticsearchRetriever\n",
        "# retriever = ElasticsearchRetriever(document_store=document_store)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YHfQWxVI0N2e",
        "outputId": "3f1925fb-e497-42ab-b3e7-3b9789869bfd"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                     Year                   Coach              Super Bowl  \\\n",
            "0                    1966          Vince Lombardi                       I   \n",
            "1                    1967          Vince Lombardi                      II   \n",
            "2                    1996           Mike Holmgren                    XXXI   \n",
            "3                    2010           Mike McCarthy                     XLV   \n",
            "4  Total Super Bowls won:  Total Super Bowls won:  Total Super Bowls won:   \n",
            "\n",
            "                  Location                Opponent  Score Record  \n",
            "0  Los Angeles, California      Kansas City Chiefs  35–10   12–2  \n",
            "1           Miami, Florida         Oakland Raiders  33–14  9–4–1  \n",
            "2   New Orleans, Louisiana    New England Patriots  35–21   13–3  \n",
            "3         Arlington, Texas     Pittsburgh Steelers  31–25   10–6  \n",
            "4   Total Super Bowls won:  Total Super Bowls won:      4      4  \n"
          ]
        }
      ],
      "source": [
        "# Try the Retriever\n",
        "from haystack.utils import print_documents\n",
        "\n",
        "retrieved_tables = retriever.retrieve(\"Who won the Super Bowl?\", top_k=5)\n",
        "# Get highest scored table\n",
        "print(retrieved_tables[0].content)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zbwkXScm2-gy"
      },
      "source": [
        "### Reader\n",
        "The `TableReader` is based on TaPas, a transformer-based language model capable of grasping the two-dimensional structure of a table. It scans the tables returned by the retriever and extracts the anser. The available TableReader models can be found [here](https://huggingface.co/models?pipeline_tag=table-question-answering&sort=downloads).\n",
        "\n",
        "**Notice**: The `TableReader` will return an answer for each table, even if the query cannot be answered by the table. Furthermore, the confidence scores are not useful as of now, given that they will *always* be very high (i.e. 1 or close to 1)."
      ]
    },
    {
      "cell_type": "code",
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      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.utils -  Using devices: CUDA\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n"
          ]
        },
        {
          "output_type": "display_data",
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          "metadata": {}
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        {
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          "data": {
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "9073fd6bb8134a8b988027177e64068e"
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        {
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              "model_id": "9d0952bb546343129c9b027ef420ed69"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from haystack.nodes import TableReader\n",
        "\n",
        "reader = TableReader(model_name_or_path=\"google/tapas-base-finetuned-wtq\", max_seq_len=512)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ILuAXkyN4F7x",
        "outputId": "1dcc269c-9dda-4da6-ad66-bf321e89d284"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                  Name        Program           Role       Salary     Year  \\\n",
            "0         Simon Cowell   The X Factor          Judge  $75 million  2012–13   \n",
            "1       Britney Spears  American Idol    $25 million      2017–18     [15]   \n",
            "2       Jennifer Lopez    $20 million        2011–12         [16]      nan   \n",
            "3         Mariah Carey    $18 million        2012–13         [17]      nan   \n",
            "4          Hugh Laurie          House  Gregory House  $15 million     2013   \n",
            "5        Ryan Seacrest  American Idol           Host      2013–16     [14]   \n",
            "6           Katy Perry   The X Factor          Judge         2012     [17]   \n",
            "7          Miley Cyrus      The Voice          Coach  $13 million  2016–17   \n",
            "8          Adam Levine        2016–18           [18]          nan      nan   \n",
            "9        Blake Shelton        2016–18           [18]          nan      nan   \n",
            "10  Christina Aguilera  $12.5 million           2013         [19]      nan   \n",
            "11      Kelly Clarkson    $12 million           2018         [20]      nan   \n",
            "12             Shakira           2013           [19]          nan      nan   \n",
            "13        Gwen Stefani           2017           [21]          nan      nan   \n",
            "14         Nicki Minaj  American Idol          Judge      2012–13     [19]   \n",
            "\n",
            "    Ref.  \n",
            "0   [14]  \n",
            "1    nan  \n",
            "2    nan  \n",
            "3    nan  \n",
            "4   [14]  \n",
            "5    nan  \n",
            "6    nan  \n",
            "7   [18]  \n",
            "8    nan  \n",
            "9    nan  \n",
            "10   nan  \n",
            "11   nan  \n",
            "12   nan  \n",
            "13   nan  \n",
            "14   nan  \n"
          ]
        }
      ],
      "source": [
        "# Try the TableReader on one Table\n",
        "\n",
        "table_doc = document_store.get_document_by_id(\"36964e90-3735-4ba1-8e6a-bec236e88bb2\")\n",
        "print(table_doc.content)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ilbsecgA4vfN",
        "outputId": "36ae04e4-12fd-4af8-c862-a39d9607f399"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: Who played Gregory House in the series House?\n",
            "Answers:\n",
            "[   <Answer {'answer': 'Hugh Laurie', 'type': 'extractive', 'score': 1.0, 'context':                   Name        Program           Role       Salary     Year  \\\n",
            "0         Simon Cowell   The X Factor          Judge  $75 million  2012–13   \n",
            "1       Britney Spears  American Idol    $25 million      2017–18     [15]   \n",
            "2       Jennifer Lopez    $20 million        2011–12         [16]      nan   \n",
            "3         Mariah Carey    $18 million        2012–13         [17]      nan   \n",
            "4          Hugh Laurie          House  Gregory House  $15 million     2013   \n",
            "5        Ryan Seacrest  American Idol           Host      2013–16     [14]   \n",
            "6           Katy Perry   The X Factor          Judge         2012     [17]   \n",
            "7          Miley Cyrus      The Voice          Coach  $13 million  2016–17   \n",
            "8          Adam Levine        2016–18           [18]          nan      nan   \n",
            "9        Blake Shelton        2016–18           [18]          nan      nan   \n",
            "10  Christina Aguilera  $12.5 million           2013         [19]      nan   \n",
            "11      Kelly Clarkson    $12 million           2018         [20]      nan   \n",
            "12             Shakira           2013           [19]          nan      nan   \n",
            "13        Gwen Stefani           2017           [21]          nan      nan   \n",
            "14         Nicki Minaj  American Idol          Judge      2012–13     [19]   \n",
            "\n",
            "    Ref.  \n",
            "0   [14]  \n",
            "1    nan  \n",
            "2    nan  \n",
            "3    nan  \n",
            "4   [14]  \n",
            "5    nan  \n",
            "6    nan  \n",
            "7   [18]  \n",
            "8    nan  \n",
            "9    nan  \n",
            "10   nan  \n",
            "11   nan  \n",
            "12   nan  \n",
            "13   nan  \n",
            "14   nan  , 'offsets_in_document': [{'start': 24, 'end': 25}], 'offsets_in_context': [{'start': 24, 'end': 25}], 'document_id': '36964e90-3735-4ba1-8e6a-bec236e88bb2', 'meta': {'aggregation_operator': 'NONE', 'answer_cells': ['Hugh Laurie']}}>]\n"
          ]
        }
      ],
      "source": [
        "from haystack.utils import print_answers\n",
        "\n",
        "prediction = reader.predict(query=\"Who played Gregory House in the series House?\", documents=[table_doc])\n",
        "print_answers(prediction, details=\"all\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jkAYNMb7R9qu"
      },
      "source": [
        "The offsets in the `offsets_in_document` and `offsets_in_context` field indicate the table cells that the model predicts to be part of the answer. They need to be interpreted on the linearized table, i.e., a flat list containing all of the table cells."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "It8XYT2ZTVJs",
        "outputId": "b31f8359-9524-4294-94fd-0bf205378dfa"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Predicted answer: Hugh Laurie\n",
            "Meta field: {'aggregation_operator': 'NONE', 'answer_cells': ['Hugh Laurie']}\n"
          ]
        }
      ],
      "source": [
        "print(f\"Predicted answer: {prediction['answers'][0].answer}\")\n",
        "print(f\"Meta field: {prediction['answers'][0].meta}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pgmG7pzL5ceh"
      },
      "source": [
        "### Pipeline\n",
        "The Retriever and the Reader can be sticked together to a pipeline in order to first retrieve relevant tables and then extract the answer.\n",
        "\n",
        "**Notice**: Given that the `TableReader` does not provide useful confidence scores and returns an answer for each of the tables, the sorting of the answers might be not helpful."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "G-aZZvyv4-Mf"
      },
      "outputs": [],
      "source": [
        "# Initialize pipeline\n",
        "from haystack import Pipeline\n",
        "\n",
        "table_qa_pipeline = Pipeline()\n",
        "table_qa_pipeline.add_node(component=retriever, name=\"TableTextRetriever\", inputs=[\"Query\"])\n",
        "table_qa_pipeline.add_node(component=reader, name=\"TableReader\", inputs=[\"TableTextRetriever\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m8evexnW6dev",
        "outputId": "e7a42384-994b-4452-d550-1d52b19b6c5f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/numpy/core/fromnumeric.py:3441: RuntimeWarning: Mean of empty slice.\n",
            "  out=out, **kwargs)\n",
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  ret = ret.dtype.type(ret / rcount)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: When was Guilty Gear Xrd : Sign released?\n",
            "Answers:\n",
            "[   {   'answer': 'December 16 , 2014',\n",
            "        'context':                                         Title       First release  \\\n",
            "0                      Guilty Gear Xrd : Sign  December 16 , 2014   \n",
            "1          BlazBlue : Chrono Phantasma Extend      June 30 , 2015   \n",
            "2         Aegis of Earth : Protonovus Assault     March 15 , 2016   \n",
            "3                  BlazBlue : Central Fiction    October 6 , 2016   \n",
            "4     Chronicles of Teddy : Harmony of Exidus     March 29 , 2016   \n",
            "5                 Guilty Gear Xrd : Revelator       June 7 , 2016   \n",
            "6   Exist Archive : The Other Side of the Sky   October 18 , 2016   \n",
            "7                     Guilty Gear Xrd : Rev 2       May 25 , 2017   \n",
            "8      Under Night In-Birth Exe : Late [ st ]           Late 2017   \n",
            "9                   School Girl/Zombie Hunter           Late 2017   \n",
            "10                           Tokyo Xanadu eX+                2017   \n",
            "11       Code : Realize ~Bouquet of Rainbows~                2018   \n",
            "12                                 Death Mark                2018   \n",
            "13                        NG ( Visual Novel )                2019   \n",
            "\n",
            "                  Developer ( s )         Platform ( s )  \n",
            "0                Arc System Works          PlayStation 4  \n",
            "1                Arc System Works          PlayStation 4  \n",
            "2                         Acquire          PlayStation 4  \n",
            "3                Arc System Works          PlayStation 4  \n",
            "4                    LookAtMyGame  PlayStation 4 ( PSN )  \n",
            "5                Arc System Works          PlayStation 4  \n",
            "6        Spike Chunsoft , tri-Ace          PlayStation 4  \n",
            "7                Arc System Works          PlayStation 4  \n",
            "8   Ecole Software , French Bread          PlayStation 4  \n",
            "9                         Tamsoft          PlayStation 4  \n",
            "10                         Falcom          PlayStation 4  \n",
            "11                        Otomate          PlayStation 4  \n",
            "12                 Experience Inc          PlayStation 4  \n",
            "13                 Experience Inc          PlayStation 4  },\n",
            "    {   'answer': 'October 7 , 2008',\n",
            "        'context':                                                            Title  \\\n",
            "0                                                Battle Fantasia   \n",
            "1                                       Guilty Gear 2 : Overture   \n",
            "2                                    BlazBlue : Calamity Trigger   \n",
            "3                                                  0-D Beat Drop   \n",
            "4                                          Record of Agarest War   \n",
            "5                                                    DeathSmiles   \n",
            "6                                     BlazBlue : Continuum Shift   \n",
            "7                                     Record of Agarest War Zero   \n",
            "8  Bit.Trip Presents ... Runner2 : Future Legend of Rhythm Alien   \n",
            "9                                 A.R.E.S : Extinction Agenda EX   \n",
            "\n",
            "         First release                    Developer ( s )     Platform ( s )  \n",
            "0  September 16 , 2008                   Arc System Works           Xbox 360  \n",
            "1     October 7 , 2008                   Arc System Works           Xbox 360  \n",
            "2       June 30 , 2009                   Arc System Works           Xbox 360  \n",
            "3   November 11 , 2009                       Cyclone Zero  Xbox 360 ( XBLA )  \n",
            "4      April 27 , 2010  Compile Heart , Red Entertainment           Xbox 360  \n",
            "5       June 28 , 2010                               Cave           Xbox 360  \n",
            "6       July 27 , 2010                   Arc System Works           Xbox 360  \n",
            "7       June 14 , 2011  Compile Heart , Red Entertainment           Xbox 360  \n",
            "8   February 27 , 2013                       Gaijin Games  Xbox 360 ( XBLA )  \n",
            "9     October 2 , 2013                      Extend Studio  Xbox 360 ( XBLA )  },\n",
            "    {   'answer': 'April 7 , 2009',\n",
            "        'context':                                       Title        First release  \\\n",
            "0           Guilty Gear XX Accent Core Plus       April 7 , 2009   \n",
            "1      BlazBlue : Calamity Trigger Portable   February 25 , 2010   \n",
            "2                            Cho Aniki Zero      March 25 , 2010   \n",
            "3                     Mimana Iyar Chronicle      March 30 , 2010   \n",
            "4                          Gladiator Begins  September 14 , 2010   \n",
            "5                    Blazing Souls Accelate    October 19 , 2010   \n",
            "6              Jikandia : The Timeless Land      March 15 , 2011   \n",
            "7             BlazBlue : Continuum Shift II        May 31 , 2011   \n",
            "8                                Fate/Extra    November 1 , 2011   \n",
            "9   Hakuoki : Demon of the Fleeting Blossom   February 14 , 2012   \n",
            "10    Hakuoki : Warriors of the Shinsengumi    November 6 , 2012   \n",
            "11                         Ragnarok Tactics   February 19 , 2013   \n",
            "12                Sweet Fuse : At Your Side     August 27 , 2013   \n",
            "\n",
            "                                     Developer ( s )  \\\n",
            "0                                   Arc System Works   \n",
            "1                                   Arc System Works   \n",
            "2                                  extreme Co. , Ltd   \n",
            "3                     Kogado Studio , Premium Agency   \n",
            "4                                             Goshow   \n",
            "5                                          Neverland   \n",
            "6                                    Opus Studio Inc   \n",
            "7                                   Arc System Works   \n",
            "8                                          Type-Moon   \n",
            "9                             Idea Factory , Otomate   \n",
            "10                                      Idea Factory   \n",
            "11  GungHo Online Entertainment , Apollosoft , Chime   \n",
            "12                  Idea Factory , Otomate , Comcept   \n",
            "\n",
            "                  Platform ( s )  \n",
            "0           PlayStation Portable  \n",
            "1           PlayStation Portable  \n",
            "2   PlayStation Portable ( PSN )  \n",
            "3           PlayStation Portable  \n",
            "4           PlayStation Portable  \n",
            "5           PlayStation Portable  \n",
            "6           PlayStation Portable  \n",
            "7           PlayStation Portable  \n",
            "8           PlayStation Portable  \n",
            "9           PlayStation Portable  \n",
            "10          PlayStation Portable  \n",
            "11          PlayStation Portable  \n",
            "12          PlayStation Portable  },\n",
            "    {   'answer': 'April 7 , 2009',\n",
            "        'context':                                       Title        First release  \\\n",
            "0           Guilty Gear XX Accent Core Plus       April 7 , 2009   \n",
            "1      BlazBlue : Calamity Trigger Portable   February 25 , 2010   \n",
            "2                            Cho Aniki Zero      March 25 , 2010   \n",
            "3                     Mimana Iyar Chronicle      March 30 , 2010   \n",
            "4                          Gladiator Begins  September 14 , 2010   \n",
            "5                    Blazing Souls Accelate    October 19 , 2010   \n",
            "6              Jikandia : The Timeless Land      March 15 , 2011   \n",
            "7             BlazBlue : Continuum Shift II        May 31 , 2011   \n",
            "8                                Fate/Extra    November 1 , 2011   \n",
            "9   Hakuoki : Demon of the Fleeting Blossom   February 14 , 2012   \n",
            "10    Hakuoki : Warriors of the Shinsengumi    November 6 , 2012   \n",
            "11                         Ragnarok Tactics   February 19 , 2013   \n",
            "12                Sweet Fuse : At Your Side     August 27 , 2013   \n",
            "\n",
            "                                     Developer ( s )  \\\n",
            "0                                   Arc System Works   \n",
            "1                                   Arc System Works   \n",
            "2                                  extreme Co. , Ltd   \n",
            "3                     Kogado Studio , Premium Agency   \n",
            "4                                             Goshow   \n",
            "5                                          Neverland   \n",
            "6                                    Opus Studio Inc   \n",
            "7                                   Arc System Works   \n",
            "8                                          Type-Moon   \n",
            "9                             Idea Factory , Otomate   \n",
            "10                                      Idea Factory   \n",
            "11  GungHo Online Entertainment , Apollosoft , Chime   \n",
            "12                  Idea Factory , Otomate , Comcept   \n",
            "\n",
            "                  Platform ( s )  \n",
            "0           PlayStation Portable  \n",
            "1           PlayStation Portable  \n",
            "2   PlayStation Portable ( PSN )  \n",
            "3           PlayStation Portable  \n",
            "4           PlayStation Portable  \n",
            "5           PlayStation Portable  \n",
            "6           PlayStation Portable  \n",
            "7           PlayStation Portable  \n",
            "8           PlayStation Portable  \n",
            "9           PlayStation Portable  \n",
            "10          PlayStation Portable  \n",
            "11          PlayStation Portable  \n",
            "12          PlayStation Portable  },\n",
            "    {   'answer': '2010',\n",
            "        'context':                   Title  Year Other artist ( s )  \\\n",
            "0          Count on You  2010      Big Time Rush   \n",
            "1    You Got ta Want It  2011                nan   \n",
            "2  Chocolate Brown Eyes  2013        Salaam Remi   \n",
            "3               Vertigo  2013       Jason Derulo   \n",
            "4               Vertigo  2014       Jason Derulo   \n",
            "5     Playing With Fire  2015       Thomas Rhett   \n",
            "6     Too Late for Love  2016         DJ Antoine   \n",
            "7            Water Guns  2016       Todrick Hall   \n",
            "8               Chasing  2017        Danny Gokey   \n",
            "\n",
            "                               Album  \n",
            "0                                BTR  \n",
            "1  Official Gameday Music of the NFL  \n",
            "2                 One in the Chamber  \n",
            "3                            Tattoos  \n",
            "4                         Talk Dirty  \n",
            "5                         Tangled Up  \n",
            "6                        Provocateur  \n",
            "7                  Straight Outta Oz  \n",
            "8                               Rise  },\n",
            "    {   'answer': '2012',\n",
            "        'context':                                   Title  Year  \\\n",
            "0                   The American Scream  2012   \n",
            "1                            Dead Souls  2012   \n",
            "2                                 Ghoul  2012   \n",
            "3                               Beneath  2013   \n",
            "4   Chilling Visions : 5 Senses of Fear  2013   \n",
            "5                     The Monkey 's Paw  2013   \n",
            "6                                Animal  2014   \n",
            "7                  Deep in the Darkness  2014   \n",
            "8                               The Boy  2015   \n",
            "9                                 SiREN  2016   \n",
            "10                       Camera Obscura  2017   \n",
            "11                          Dementia 13  2017   \n",
            "\n",
            "                                                   Production Co  \n",
            "0                                 Chiller Films Brainstorm Media  \n",
            "1                            Chiller Films Synthetic Productions  \n",
            "2                                       Chiller Films Modernciné  \n",
            "3                                                  Glass Eye Pix  \n",
            "4                   Chiller Films Synthetic Cinema International  \n",
            "5                                                      TMP Films  \n",
            "6                    Flower Films Synthetic Cinema International  \n",
            "7                   Chiller Films Synthetic Cinema International  \n",
            "8                                                  SpectreVision  \n",
            "9                                                       Studio71  \n",
            "10  Chiller Films Hood River Entertainment Paper Street Pictures  \n",
            "11                            Pipeline Entertainment Haloran LLC  },\n",
            "    {   'answer': 'November 15 , 2007',\n",
            "        'context':                                     Title        First release  \\\n",
            "0            Hooked ! Real Motion Fishing    October 30 , 2007   \n",
            "1              Guilty Gear XX Accent Core   November 15 , 2007   \n",
            "2           MiniCopter : Adventure Flight      April 11 , 2008   \n",
            "3                       River City Ransom      April 21 , 2008   \n",
            "4                           Double Dragon      April 28 , 2008   \n",
            "5                                Renegade         May 5 , 2008   \n",
            "6                 Castle of Shikigami III        May 13 , 2008   \n",
            "7                     Family Table Tennis        May 26 , 2008   \n",
            "8                        Super Dodge Ball  September 22 , 2008   \n",
            "9                     Family Glide Hockey    January 19 , 2009   \n",
            "10                          Bit.Trip Beat      March 16 , 2009   \n",
            "11                    Family Pirate Party        May 11 , 2009   \n",
            "12        Guilty Gear XX Accent Core Plus        May 12 , 2009   \n",
            "13                       Family Mini Golf       June 22 , 2009   \n",
            "14                          Bit.Trip Core        July 6 , 2009   \n",
            "15                 Family Slot Car Racing     August 17 , 2009   \n",
            "16  Crash ' n the Boys : Street Challenge  September 14 , 2009   \n",
            "17                          Family Tennis  September 21 , 2009   \n",
            "18                      Family Card Games    November 2 , 2009   \n",
            "19   Hooked ! Again : Real Motion Fishing    November 3 , 2009   \n",
            "\n",
            "     Developer ( s )           Platform ( s )  \n",
            "0               SIMS                      Wii  \n",
            "1   Arc System Works                      Wii  \n",
            "2      Sonic Powered                      Wii  \n",
            "3            Technos  Wii ( Virtual Console )  \n",
            "4            Technos  Wii ( Virtual Console )  \n",
            "5            Technos  Wii ( Virtual Console )  \n",
            "6        Alfa System                      Wii  \n",
            "7   Arc System Works          Wii ( WiiWare )  \n",
            "8            Technos  Wii ( Virtual Console )  \n",
            "9   Arc System Works          Wii ( WiiWare )  \n",
            "10      Gaijin Games          Wii ( WiiWare )  \n",
            "11  Arc System Works          Wii ( WiiWare )  \n",
            "12  Arc System Works                      Wii  \n",
            "13  Arc System Works          Wii ( WiiWare )  \n",
            "14      Gaijin Games          Wii ( WiiWare )  \n",
            "15  Arc System Works          Wii ( WiiWare )  \n",
            "16           Technos  Wii ( Virtual Console )  \n",
            "17  Arc System Works          Wii ( WiiWare )  \n",
            "18  Arc System Works          Wii ( WiiWare )  \n",
            "19    SIMS Co. , Ltd                      Wii  },\n",
            "    {   'answer': '',\n",
            "        'context':                              Game          Publisher         Release Date  \\\n",
            "0                  Super Mario 64           Nintendo  September 26 , 1996   \n",
            "1                 Wipeout XL/2097          Psygnosis  September 30 , 1996   \n",
            "2                           Quake     GT Interactive       June 22 , 1996   \n",
            "3                 Civilization II         MicroProse   February 29 , 1996   \n",
            "4                        Tekken 2              Namco     August 25 , 1996   \n",
            "5                    Wave Race 64           Nintendo    November 1 , 1996   \n",
            "6          Realms of the Haunting          Interplay   December 31 , 1996   \n",
            "7                     Tomb Raider  Eidos Interactive    October 25 , 1996   \n",
            "8                   Resident Evil             Capcom      March 30 , 1996   \n",
            "9   Command & Conquer : Red Alert             Virgin   November 22 , 1996   \n",
            "10                   Dragon Force               Sega   November 30 , 1996   \n",
            "11                Guardian Heroes               Sega    January 25 , 1996   \n",
            "12                Super Mario RPG           Nintendo       March 9 , 1996   \n",
            "13                  Duke Nukem 3D     GT Interactive    January 29 , 1996   \n",
            "14             NiGHTS into Dreams               Sega        July 5 , 1996   \n",
            "15                  Pilotwings 64           Nintendo  September 26 , 1996   \n",
            "16         Panzer Dragoon II Zwei               Sega      March 22 , 1996   \n",
            "\n",
            "       Platform ( s ) MC score GR score  \n",
            "0         Nintendo 64   94/100   96.41%  \n",
            "1         PlayStation   93/100   94.75%  \n",
            "2                 DOS   94/100   93.22%  \n",
            "3   Microsoft Windows   94/100   91.29%  \n",
            "4         PlayStation   89/100   92.50%  \n",
            "5         Nintendo 64   92/100   90.67%  \n",
            "6   Microsoft Windows      nan   91.86%  \n",
            "7         PlayStation   91/100   90.02%  \n",
            "8         PlayStation   91/100   87.23%  \n",
            "9                 DOS   90/100   90.91%  \n",
            "10        Sega Saturn      nan   89.64%  \n",
            "11        Sega Saturn      nan   89.20%  \n",
            "12               SNES      nan   89.12%  \n",
            "13                DOS   89/100   88.50%  \n",
            "14        Sega Saturn      nan   88.56%  \n",
            "15        Nintendo 64   80/100   87.52%  \n",
            "16        Sega Saturn      nan   87.50%  },\n",
            "    {   'answer': '',\n",
            "        'context':                              Game          Publisher         Release Date  \\\n",
            "0                  Super Mario 64           Nintendo  September 26 , 1996   \n",
            "1                 Wipeout XL/2097          Psygnosis  September 30 , 1996   \n",
            "2                           Quake     GT Interactive       June 22 , 1996   \n",
            "3                 Civilization II         MicroProse   February 29 , 1996   \n",
            "4                        Tekken 2              Namco     August 25 , 1996   \n",
            "5                    Wave Race 64           Nintendo    November 1 , 1996   \n",
            "6          Realms of the Haunting          Interplay   December 31 , 1996   \n",
            "7                     Tomb Raider  Eidos Interactive    October 25 , 1996   \n",
            "8                   Resident Evil             Capcom      March 30 , 1996   \n",
            "9   Command & Conquer : Red Alert             Virgin   November 22 , 1996   \n",
            "10                   Dragon Force               Sega   November 30 , 1996   \n",
            "11                Guardian Heroes               Sega    January 25 , 1996   \n",
            "12                Super Mario RPG           Nintendo       March 9 , 1996   \n",
            "13                  Duke Nukem 3D     GT Interactive    January 29 , 1996   \n",
            "14             NiGHTS into Dreams               Sega        July 5 , 1996   \n",
            "15                  Pilotwings 64           Nintendo  September 26 , 1996   \n",
            "16         Panzer Dragoon II Zwei               Sega      March 22 , 1996   \n",
            "\n",
            "       Platform ( s ) MC score GR score  \n",
            "0         Nintendo 64   94/100   96.41%  \n",
            "1         PlayStation   93/100   94.75%  \n",
            "2                 DOS   94/100   93.22%  \n",
            "3   Microsoft Windows   94/100   91.29%  \n",
            "4         PlayStation   89/100   92.50%  \n",
            "5         Nintendo 64   92/100   90.67%  \n",
            "6   Microsoft Windows      nan   91.86%  \n",
            "7         PlayStation   91/100   90.02%  \n",
            "8         PlayStation   91/100   87.23%  \n",
            "9                 DOS   90/100   90.91%  \n",
            "10        Sega Saturn      nan   89.64%  \n",
            "11        Sega Saturn      nan   89.20%  \n",
            "12               SNES      nan   89.12%  \n",
            "13                DOS   89/100   88.50%  \n",
            "14        Sega Saturn      nan   88.56%  \n",
            "15        Nintendo 64   80/100   87.52%  \n",
            "16        Sega Saturn      nan   87.50%  },\n",
            "    {   'answer': 'April\\xa026,\\xa02018',\n",
            "        'context':    No. overall No. in season                   Title          Directed by  \\\n",
            "0           45             1   The Conscience Code\"\"     Russell Lee Fine   \n",
            "1           46             2        Fear and Flesh\"\"  Alexandra Kalymnios   \n",
            "2           47             3           Hell's Gate\"\"   Constantine Makris   \n",
            "3           48             4             Spy Games\"\"       Kevin Sullivan   \n",
            "4           49             5    The Blood of Romeo\"\"      David McWhirter   \n",
            "5           50             6      The Heavens Fall\"\"     Russell Lee Fine   \n",
            "6           51             7      Bullet Train\"[10]\"           Rob Bowman   \n",
            "7           52             8        Deep Cover\"[10]\"            Jim McKay   \n",
            "8           53             9     Fear Feargach\"[10]\"          P. J. Pesce   \n",
            "9           54            10  No Place Is Home\"[10]\"         Kenneth Fink   \n",
            "10          55            11    The Art of War\"[10]\"       Jennifer Phang   \n",
            "11          56            12            Ghosts\"[10]\"     Russell Lee Fine   \n",
            "12          57            13      Who Are You?\"[10]\"     Russell Lee Fine   \n",
            "\n",
            "                          Written by Original air date [3]  \\\n",
            "0                   Michael Seitzman        April 26, 2018   \n",
            "1                      Dave Kalstein           May 3, 2018   \n",
            "2                         Tom Mularz          May 10, 2018   \n",
            "3                        Julia Cohen          May 25, 2018   \n",
            "4                         Adam Armus          June 1, 2018   \n",
            "5            Michael Brandon Guercio         June 15, 2018   \n",
            "6           Tom Mularz & Gideon Yago         June 22, 2018   \n",
            "7            Cole Maliska & Joe Webb         June 29, 2018   \n",
            "8       Dave Kalstein & Matthew Klam          July 6, 2018   \n",
            "9      Gisselle Legere & Julia Cohen         July 13, 2018   \n",
            "10           Adam Armus & Tom Mularz         July 20, 2018   \n",
            "11        Julia Cohen & Matthew Klam         July 27, 2018   \n",
            "12  Dave Kalstein & Michael Seitzman        August 3, 2018   \n",
            "\n",
            "   U.S. viewers (millions)  \n",
            "0                  2.66[4]  \n",
            "1                  2.15[5]  \n",
            "2                  1.97[6]  \n",
            "3                  2.62[7]  \n",
            "4                  2.99[8]  \n",
            "5                  2.56[9]  \n",
            "6                      TBD  \n",
            "7                      TBD  \n",
            "8                      TBD  \n",
            "9                      TBD  \n",
            "10                     TBD  \n",
            "11                     TBD  \n",
            "12                     TBD  },\n",
            "    {   'answer': \"Don't Push It\",\n",
            "        'context':    Position                Name               Rider Age Weight Starting price  \\\n",
            "0       1st       Don't Push It          Tony McCoy  10  11-05        10/1 JF   \n",
            "1       2nd      Black Apalachi       Denis O'Regan  11  11-06           14/1   \n",
            "2       3rd       State of Play        Paul Moloney  10  10-11           16/1   \n",
            "3       4th    Big Fella Thanks      Barry Geraghty   8  10-12        10/1 JF   \n",
            "4       5th           Hello Bud  Sam Twiston-Davies  12  10-06           20/1   \n",
            "5       6th       Snowy Morning         David Casey  10  10-13           14/1   \n",
            "6       7th  Character Building       Nina Carberry  10  10-11           16/1   \n",
            "7       8th         Cloudy Lane       Jason Maguire  10  11-03           25/1   \n",
            "8       9th    Tricky Trickster     Richard Johnson   7  11-04           16/1   \n",
            "9      10th          Joe Lively         Joe Tizzard  11  11-06           33/1   \n",
            "10     11th              Cerium        Davy Russell   9  10-06           50/1   \n",
            "11     12th       Comply or Die        Timmy Murphy  11  10-05           12/1   \n",
            "12     13th              Piraya     Johnny Farrelly   7  10-07          100/1   \n",
            "\n",
            "               Distance Prize money  \n",
            "0   Winner by 5 lengths    £521,052  \n",
            "1             5 lengths    £196,285  \n",
            "2            20 lengths     £98,235  \n",
            "3             3 lengths     £49,117  \n",
            "4             7 lengths     £24,605  \n",
            "5            1½ lengths     £12,302  \n",
            "6                  Neck      £6,105  \n",
            "7            12 lengths      £3,145  \n",
            "8              ¾ length         Nil  \n",
            "9            Short head         Nil  \n",
            "10           A distance         Nil  \n",
            "11            8 lengths         Nil  \n",
            "12           A distance         Nil  },\n",
            "    {   'answer': '5 June 2009',\n",
            "        'context':   Episode First broadcast                             Seans team  \\\n",
            "0    8x01     5 June 2009             Johnny Vegas and Alex Zane   \n",
            "1    8x02    12 June 2009    Jeremy Clarkson and James McQuillan   \n",
            "2    8x03    19 June 2009                 Josie Long and Jamelia   \n",
            "3    8x04    26 June 2009        Tom Felton and Richard E. Grant   \n",
            "4    8x05     3 July 2009     Yvette Fielding and David Walliams   \n",
            "5    8x06    10 July 2009  Reginald D. Hunter and Kelly Osbourne   \n",
            "6    8x07    17 July 2009       Kevin Bridges and Patrick Kielty   \n",
            "\n",
            "                           Jasons team Scores  \n",
            "0    Ulrika Jonsson and Jack Whitehall    5–5  \n",
            "1       David Walliams and Holly Walsh    2–7  \n",
            "2    Mark Watson and Claudia Winkleman    4–4  \n",
            "3      Alan Cumming and Lauren Laverne    4–2  \n",
            "4  Reginald D. Hunter and Phil Spencer    5–4  \n",
            "5       Terry Christian and Isy Suttie    4–6  \n",
            "6    Rhod Gilbert and Shappi Khorsandi    3–7  },\n",
            "    {   'answer': '2017',\n",
            "        'context':     Year                     Title                       Role  \\\n",
            "0   2017   Mass Effect : Andromeda                    Various   \n",
            "1   2017                 Lone Echo                       Hera   \n",
            "2   2017  Madden NFL 18 : Longshot                    Various   \n",
            "3   2017                   FIFA 18          Beatriz Villanova   \n",
            "4   2017            Puzzle Fighter          Additional Voices   \n",
            "5   2017    Need for Speed Payback          Additional Voices   \n",
            "6   2018             Dragalia Lost  Corsaint Phoenix / Kristy   \n",
            "7   2018                   FIFA 19          Beatriz Villanova   \n",
            "8   2019               Crackdown 3          Additional Voices   \n",
            "9   2019                    Anthem              Princess Zhim   \n",
            "10  2019                   FIFA 20          Beatriz Villanova   \n",
            "\n",
            "                        Notes  \n",
            "0   Performance Capture Actor  \n",
            "1                Voice acting  \n",
            "2        Motion capture actor  \n",
            "3                Voice acting  \n",
            "4                         nan  \n",
            "5                         nan  \n",
            "6                Voice acting  \n",
            "7                Voice acting  \n",
            "8                         nan  \n",
            "9                Voice acting  \n",
            "10               Voice acting  },\n",
            "    {   'answer': '2017',\n",
            "        'context':     Year                     Title                       Role  \\\n",
            "0   2017   Mass Effect : Andromeda                    Various   \n",
            "1   2017                 Lone Echo                       Hera   \n",
            "2   2017  Madden NFL 18 : Longshot                    Various   \n",
            "3   2017                   FIFA 18          Beatriz Villanova   \n",
            "4   2017            Puzzle Fighter          Additional Voices   \n",
            "5   2017    Need for Speed Payback          Additional Voices   \n",
            "6   2018             Dragalia Lost  Corsaint Phoenix / Kristy   \n",
            "7   2018                   FIFA 19          Beatriz Villanova   \n",
            "8   2019               Crackdown 3          Additional Voices   \n",
            "9   2019                    Anthem              Princess Zhim   \n",
            "10  2019                   FIFA 20          Beatriz Villanova   \n",
            "\n",
            "                        Notes  \n",
            "0   Performance Capture Actor  \n",
            "1                Voice acting  \n",
            "2        Motion capture actor  \n",
            "3                Voice acting  \n",
            "4                         nan  \n",
            "5                         nan  \n",
            "6                Voice acting  \n",
            "7                Voice acting  \n",
            "8                         nan  \n",
            "9                Voice acting  \n",
            "10               Voice acting  },\n",
            "    {   'answer': '7 May 2013 (hardcover)',\n",
            "        'context':      #                  Title      Publisher  \\\n",
            "0    1        Dead Until Dark      Ace Books   \n",
            "1    2  Living Dead in Dallas      Ace Books   \n",
            "2    3              Club Dead      Ace Books   \n",
            "3    4      Dead to the World  Ace Hardcover   \n",
            "4    5     Dead as a Doornail  Ace Hardcover   \n",
            "5    6        Definitely Dead  Ace Hardcover   \n",
            "6    7      All Together Dead  Ace Hardcover   \n",
            "7    8     From Dead to Worse  Ace Hardcover   \n",
            "8    9          Dead and Gone  Ace Hardcover   \n",
            "9   10     Dead in the Family  Ace Hardcover   \n",
            "10  11         Dead Reckoning  Ace Hardcover   \n",
            "11  12             Deadlocked  Ace Hardcover   \n",
            "12  13        Dead Ever After  Ace Hardcover   \n",
            "\n",
            "                                            Release  Length  \\\n",
            "0     May 2001 (paperback) January 2008 (hardcover)  291 pp   \n",
            "1   April 2002 (paperback) January 2009 (hardcover)  291 pp   \n",
            "2       May 2003 (paperback) March 2010 (hardcover)  292 pp   \n",
            "3         May 2004 (hardcover) May 2005 (paperback)  291 pp   \n",
            "4       May 2005 (hardcover) April 2006 (paperback)  295 pp   \n",
            "5       May 2006 (hardcover) March 2007 (paperback)  324 pp   \n",
            "6       May 2007 (hardcover) March 2008 (paperback)  336 pp   \n",
            "7       May 2008 (hardcover) March 2009 (paperback)  359 pp   \n",
            "8       May 2009 (hardcover) April 2010 (paperback)  312 pp   \n",
            "9       May 2010 (hardcover) March 2011 (paperback)  311 pp   \n",
            "10      May 2011 (hardcover) March 2012 (paperback)  325 pp   \n",
            "11      May 2012 (hardcover) March 2013 (paperback)  336 pp   \n",
            "12                           7 May 2013 (hardcover)  352 pp   \n",
            "\n",
            "             Hardcover           Paperback  \n",
            "0   ISBN 0-441-01597-2  ISBN 0-441-00853-4  \n",
            "1   ISBN 0-441-01673-1  ISBN 0-441-00923-9  \n",
            "2   ISBN 0-441-01910-2  ISBN 0-441-01051-2  \n",
            "3   ISBN 0-441-01167-5  ISBN 0-441-01218-3  \n",
            "4   ISBN 0-441-01279-5  ISBN 0-441-01333-3  \n",
            "5   ISBN 0-441-01400-3  ISBN 0-441-01491-7  \n",
            "6   ISBN 0-441-01494-1  ISBN 0-441-01581-6  \n",
            "7   ISBN 0-441-01589-1  ISBN 0-441-01701-0  \n",
            "8   ISBN 0-441-01715-0  ISBN 0-441-01851-3  \n",
            "9   ISBN 0-441-01864-5  ISBN 0-441-02015-1  \n",
            "10  ISBN 0-441-02031-3  ISBN 0-441-02060-7  \n",
            "11  ISBN 1-937007-44-8  ISBN 0-425-25638-3  \n",
            "12     ISBN 193700788X            ISBN n/a  },\n",
            "    {   'answer': '2',\n",
            "        'context':   Pos                                 Artist  \\\n",
            "0   1  Daniel Lavoie , Patrick Fiori & Garou   \n",
            "1   2                                  Manau   \n",
            "2   3                            Céline Dion   \n",
            "3   4                                   Lââm   \n",
            "4   5                                 Nomads   \n",
            "5   6                      Hermes House Band   \n",
            "6   7                        Brandy & Monica   \n",
            "7   8                      Ménélik & Imane D   \n",
            "8   9                           Ricky Martin   \n",
            "9  10                                Des'ree   \n",
            "\n",
            "                                         Title     Sales*  \n",
            "0                                        Belle  2,221,000  \n",
            "1                             La Tribu de Dana  1,415,000  \n",
            "2                          My Heart Will Go On  1,197,000  \n",
            "3  Chanter pour ceux qui sont loin de chez eux    963,000  \n",
            "4                                     Yakalelo    846,000  \n",
            "5                               I Will Survive    812,000  \n",
            "6                              The Boy Is Mine    662,000  \n",
            "7                                      Bye bye    613,000  \n",
            "8                           La Copa De La Vida    563,000  \n",
            "9                                         Life    555,000  },\n",
            "    {   'answer': '2005',\n",
            "        'context':        Year                                          Title  \\\n",
            "0      2005                            Kiss Kiss Bang Bang   \n",
            "1      2006                                       Bambi II   \n",
            "2      2006                                 Curious George   \n",
            "3      2006                          Ice Age: The Meltdown   \n",
            "4      2006                                 Over the Hedge   \n",
            "5      2006                                        Grilled   \n",
            "6      2008                                One Missed Call   \n",
            "7      2008                            Horton Hears a Who!   \n",
            "8      2008                                    Speed Racer   \n",
            "9      2009       Tales from the Catholic Church of Elvis!   \n",
            "10     2009    Final Fantasy VII: Advent Children Complete   \n",
            "11     2009                       Life Is Hot in Cracktown   \n",
            "12     2009                                         Duress   \n",
            "13     2009                                   Opposite Day   \n",
            "14     2009              Cloudy with a Chance of Meatballs   \n",
            "15     2009                     Afro Samurai: Resurrection   \n",
            "16     2010                                        Killers   \n",
            "17     2010                     Nic & Tristan Go Mega Dega   \n",
            "18     2010                       DC Showcase: Green Arrow   \n",
            "19     2011                    Chaperone, TheThe Chaperone   \n",
            "20     2011     Phineas and Ferb: Across the 2nd Dimension   \n",
            "21     2011               Fred 2: Night of the Living Fred   \n",
            "22     2012                                       Excision   \n",
            "23     2012                                     ParaNorman   \n",
            "24  2012/13  Batman: The Dark Knight Returns – Parts 1 & 2   \n",
            "25     2012          Sofia the First: Once Upon a Princess   \n",
            "26     2013    Dora the Explorer and the Destiny Medallion   \n",
            "27     2013                       Scooby-Doo! Stage Fright   \n",
            "28     2013           Sofia the First: The Floating Palace   \n",
            "29     2013                         Tad, The Lost Explorer   \n",
            "30     2014                          Mr. Peabody & Sherman   \n",
            "31     2015                                      Safelight   \n",
            "32     2016                 Elena and the Secret of Avalor   \n",
            "33     2017                       Smurfs: The Lost Village   \n",
            "34     2017                            The Last Movie Star   \n",
            "\n",
            "                             Role  \\\n",
            "0        Young Harmony Faith Lane   \n",
            "1                Thumper's sister   \n",
            "2                             Kid   \n",
            "3              Various characters   \n",
            "4               Additional voices   \n",
            "5                           Dolly   \n",
            "6                    Ellie Layton   \n",
            "7              Various characters   \n",
            "8            Young Trixie Shimura   \n",
            "9                     Little girl   \n",
            "10                Marlene Wallace   \n",
            "11                          Suzie   \n",
            "12                  Sarah Barnett   \n",
            "13                   Carla Benson   \n",
            "14             Various characters   \n",
            "15                      Young Sio   \n",
            "16                          Sadie   \n",
            "17                           Lisa   \n",
            "18               Princess Perdita   \n",
            "19                          Sally   \n",
            "20  Gretchen / Various characters   \n",
            "21                          Talia   \n",
            "22                          Grace   \n",
            "23            Blithe Hollow – kid   \n",
            "24    Carrie Kelley/Robin (voice)   \n",
            "25                          Sofia   \n",
            "26                           Dora   \n",
            "27                  Chrissy Damon   \n",
            "28                          Sofia   \n",
            "29                    Sara Lavrof   \n",
            "30                 Penny Peterson   \n",
            "31                           Kate   \n",
            "32                          Sofia   \n",
            "33                     Smurf Lily   \n",
            "34                            Lil   \n",
            "\n",
            "                                              Notes  \n",
            "0                                               nan  \n",
            "1                                        Voice role  \n",
            "2                                        Voice role  \n",
            "3                                        Voice role  \n",
            "4                                        Voice role  \n",
            "5                                               nan  \n",
            "6                                               nan  \n",
            "7                                        Voice role  \n",
            "8                                               nan  \n",
            "9                                               nan  \n",
            "10                                       Voice role  \n",
            "11                                              nan  \n",
            "12                                              nan  \n",
            "13                                              nan  \n",
            "14                                       Voice role  \n",
            "15                                       Voice role  \n",
            "16                                              nan  \n",
            "17                                              nan  \n",
            "18                                       Voice role  \n",
            "19                                              nan  \n",
            "20                                       Voice role  \n",
            "21                                              nan  \n",
            "22                                              nan  \n",
            "23                                       Voice role  \n",
            "24  Direct-to-video; originally released separately  \n",
            "25                                       Voice role  \n",
            "26        YouTube short film series by CollegeHumor  \n",
            "27                                       Voice role  \n",
            "28                                       Voice role  \n",
            "29                                       Voice role  \n",
            "30                                       Voice role  \n",
            "31                                              nan  \n",
            "32                                       Voice role  \n",
            "33                                       Voice role  \n",
            "34                                              nan  },\n",
            "    {   'answer': '2',\n",
            "        'context':   Number                                    Album              Artist  \\\n",
            "0      1                            Tha Carter IV           Lil Wayne   \n",
            "1      2                                Take Care               Drake   \n",
            "2      3                         Watch the Throne  Jay-Z & Kanye West   \n",
            "3      4  Thug Motivation 103 : Hustlerz Ambition         Young Jeezy   \n",
            "4      5          Cole World : The Sideline Story             J. Cole   \n",
            "5      6                                   Lasers         Lupe Fiasco   \n",
            "6      7                           Rolling Papers         Wiz Khalifa   \n",
            "7      8                        Hell : The Sequel      Bad Meets Evil   \n",
            "8      9                                 Ambition                Wale   \n",
            "9     10                          Blue Slide Park          Mac Miller   \n",
            "\n",
            "  1st-week sales 1st-week position  \n",
            "0        964,000                 1  \n",
            "1        631,000                 1  \n",
            "2        436,000                 1  \n",
            "3        233,000                 3  \n",
            "4        217,000                 1  \n",
            "5        204,000                 1  \n",
            "6        197,000                 2  \n",
            "7        171,000                 1  \n",
            "8        164,000                 2  \n",
            "9        144,000                 1  },\n",
            "    {   'answer': '15 April 2005',\n",
            "        'context':       Release date                  Release title    Country      Publisher  \\\n",
            "0   1 January 2000  Martial Law: Shanghai Express  Hong Kong  Deltamac (HK)   \n",
            "1    15 April 2005     Martial Law: Diamond Fever  Hong Kong  Deltamac (HK)   \n",
            "2    15 April 2005      Martial Law: Dead Ringers  Hong Kong  Deltamac (HK)   \n",
            "3    15 April 2005       Martial Law: Funny Money  Hong Kong  Deltamac (HK)   \n",
            "4    15 April 2005   Martial Law: Extreme Mesures  Hong Kong  Deltamac (HK)   \n",
            "5    15 April 2005         Martial Law: Trackdown  Hong Kong  Deltamac (HK)   \n",
            "6    15 April 2005          Martial Law: Take Out  Hong Kong  Deltamac (HK)   \n",
            "7    15 April 2005           Martial Law: Lock-Up  Hong Kong  Deltamac (HK)   \n",
            "8    15 April 2005       Martial Law: Substitutes  Hong Kong  Deltamac (HK)   \n",
            "9    15 April 2005          Martial Law: Trifecta  Hong Kong  Deltamac (HK)   \n",
            "10   15 April 2005         Martial Law Collection  Hong Kong  Deltamac (HK)   \n",
            "\n",
            "   Format Language            Subtitles     Notes  \n",
            "0    NTSC  English  Traditional Chinese     1 VCD  \n",
            "1    NTSC  English  Traditional Chinese     1 VCD  \n",
            "2    NTSC  English  Traditional Chinese     1 VCD  \n",
            "3    NTSC  English  Traditional Chinese     1 VCD  \n",
            "4    NTSC  English  Traditional Chinese     1 VCD  \n",
            "5    NTSC  English  Traditional Chinese     1 VCD  \n",
            "6    NTSC  English  Traditional Chinese     1 VCD  \n",
            "7    NTSC  English  Traditional Chinese     1 VCD  \n",
            "8    NTSC  English  Traditional Chinese     1 VCD  \n",
            "9    NTSC  English  Traditional Chinese     1 VCD  \n",
            "10   NTSC  English  Traditional Chinese  10 VCD's  },\n",
            "    {   'answer': '15 April 2005',\n",
            "        'context':       Release date                  Release title    Country      Publisher  \\\n",
            "0   1 January 2000  Martial Law: Shanghai Express  Hong Kong  Deltamac (HK)   \n",
            "1    15 April 2005     Martial Law: Diamond Fever  Hong Kong  Deltamac (HK)   \n",
            "2    15 April 2005      Martial Law: Dead Ringers  Hong Kong  Deltamac (HK)   \n",
            "3    15 April 2005       Martial Law: Funny Money  Hong Kong  Deltamac (HK)   \n",
            "4    15 April 2005   Martial Law: Extreme Mesures  Hong Kong  Deltamac (HK)   \n",
            "5    15 April 2005         Martial Law: Trackdown  Hong Kong  Deltamac (HK)   \n",
            "6    15 April 2005          Martial Law: Take Out  Hong Kong  Deltamac (HK)   \n",
            "7    15 April 2005           Martial Law: Lock-Up  Hong Kong  Deltamac (HK)   \n",
            "8    15 April 2005       Martial Law: Substitutes  Hong Kong  Deltamac (HK)   \n",
            "9    15 April 2005          Martial Law: Trifecta  Hong Kong  Deltamac (HK)   \n",
            "10   15 April 2005         Martial Law Collection  Hong Kong  Deltamac (HK)   \n",
            "\n",
            "   Format Language            Subtitles     Notes  \n",
            "0    NTSC  English  Traditional Chinese     1 VCD  \n",
            "1    NTSC  English  Traditional Chinese     1 VCD  \n",
            "2    NTSC  English  Traditional Chinese     1 VCD  \n",
            "3    NTSC  English  Traditional Chinese     1 VCD  \n",
            "4    NTSC  English  Traditional Chinese     1 VCD  \n",
            "5    NTSC  English  Traditional Chinese     1 VCD  \n",
            "6    NTSC  English  Traditional Chinese     1 VCD  \n",
            "7    NTSC  English  Traditional Chinese     1 VCD  \n",
            "8    NTSC  English  Traditional Chinese     1 VCD  \n",
            "9    NTSC  English  Traditional Chinese     1 VCD  \n",
            "10   NTSC  English  Traditional Chinese  10 VCD's  },\n",
            "    {   'answer': '1991',\n",
            "        'context':     Year                 Film                       Song  \\\n",
            "0   1991        House Party 2  Ai n't Gon na Hurt Nobody   \n",
            "1   1991  Nothing But Trouble                  Same Song   \n",
            "2   1994        Above the Rim                   Regulate   \n",
            "3   1994       Street Fighter      Something Kinda Funky   \n",
            "4   1995               Friday    Keep Their Heads Ringin   \n",
            "5   1999         Office Space      Shove This Jay-Oh-Bee   \n",
            "6   2001             The Wash             Bad Intentions   \n",
            "7   2002               8 Mile              Lose Yourself   \n",
            "8   2002            Like Mike                 Basketball   \n",
            "9   2002            Like Mike               Take Ya Home   \n",
            "10  2003     2 Fast 2 Furious                 Act a Fool   \n",
            "\n",
            "                                                        Artist  \n",
            "0                                                 Kid ' n Play  \n",
            "1                                 Digital Underground ft. 2Pac  \n",
            "2                                       Warren G ft. Nate Dogg  \n",
            "3                                                    Rally Ral  \n",
            "4                                                      Dr. Dre  \n",
            "5                                       Canibus and Biz Markie  \n",
            "6                                     Dr. Dre ft. Knoc-turn'al  \n",
            "7                                                       Eminem  \n",
            "8   Lil ' Bow Wow ft. Fundisha , Jermaine Dupri , and Fabolous  \n",
            "9                                                Lil ' Bow Wow  \n",
            "10                                                    Ludacris  },\n",
            "    {   'answer': '1987 1988 1989',\n",
            "        'context':                                                  Title            Year  \\\n",
            "0                            Bomber King / RoboWarrior  1987 1988 1989   \n",
            "1     Bomber King : Scenario 2 / Blaster Master Boy/Jr       1991 1992   \n",
            "2                             Bomberman : Panic Bomber       1994 1995   \n",
            "3                                    Bomberman B-Daman            1996   \n",
            "4                                     Atomic Bomberman            1997   \n",
            "5                                       Bomberman Wars            1998   \n",
            "6                               Bomberman Fantasy Race  1998 1999 2000   \n",
            "7   Bomberman B-Daman Bakugaiden : The Road to Victory            1999   \n",
            "8     Bomberman B-Daman Bakugaiden V : Final Mega Tune            2000   \n",
            "9                                       Bomberman Kart       2001 2003   \n",
            "10         Bomberman Jetters : The Legendary Bomberman            2002   \n",
            "11                                   Bomberman Jetters       2002 2004   \n",
            "12                   Bomberman Jetters Game Collection            2003   \n",
            "13                          DreamMix TV World Fighters            2003   \n",
            "14                                         BoBomberman            2004   \n",
            "15              Bomberman Battles / Bomberman Hardball       2004 2005   \n",
            "16                Bomberman : Bakufuu Sentai Bombermen            2006   \n",
            "17                                Bomberman : Act Zero            2006   \n",
            "18                   Bomberman : Disney Stitch Edition            2010   \n",
            "19                                  Bomberman : Chains            2011   \n",
            "\n",
            "                                                                          Platforms  \\\n",
            "0                                                               Famicom / NES , MSX   \n",
            "1                                                                          Game Boy   \n",
            "2   PC Engine CD , Neo Geo , Super Famicom , NEC PC-9821 , FM Towns , Sharp X680...   \n",
            "3                                                                     Super Famicom   \n",
            "4                                                                    PC ( Windows )   \n",
            "5                                                         PlayStation , Sega Saturn   \n",
            "6                                                                       PlayStation   \n",
            "7                                                                    Game Boy Color   \n",
            "8                                                                    Game Boy Color   \n",
            "9                                                                     PlayStation 2   \n",
            "10                                                                 Game Boy Advance   \n",
            "11                                                         GameCube , PlayStation 2   \n",
            "12                                                                 Game Boy Advance   \n",
            "13                                                         GameCube , PlayStation 2   \n",
            "14                                                                 Game Boy Advance   \n",
            "15                                                                    PlayStation 2   \n",
            "16                                                             PlayStation Portable   \n",
            "17                                                                         Xbox 360   \n",
            "18                                                                     Mobile Phone   \n",
            "19                                                                              iOS   \n",
            "\n",
            "                                                                              Notes  \n",
            "0   Released outside Japan under the name RoboWarrior ; Bomberman-like progressi...  \n",
            "1   Sequel to Bomber King ; slightly altered and released by Sunsoft in America ...  \n",
            "2   Puzzle game , similar to Puyo Puyo and Tetris ; all versions except for Neo ...  \n",
            "3                                           Japan-only , part of the B-Daman series  \n",
            "4   10-player support through IPX networking ; first Bomberman title for Windows...  \n",
            "5                          Japan-only release ; tactical role-playing game ( TRPG )  \n",
            "6                                                                       Racing game  \n",
            "7   Japan-only release ; based on the anime series , Bomberman B-Daman Bakugaide...  \n",
            "8   Japan-only release ; based on the anime series , Bomberman B-Daman Bakugaide...  \n",
            "9                         Released in Japan and PAL regions only ; kart racing game  \n",
            "10               Japan-only release ; based on the anime series , Bomberman Jetters  \n",
            "11         PS2 release was Japan-only ; based on the Bomberman Jetters anime series  \n",
            "12               Japan-only release ; based on the anime series , Bomberman Jetters  \n",
            "13  Released in Japan only ; crossover fighting game featuring Bomberman as a pl...  \n",
            "14  Minigame based on the NES version of Bomberman , but using characters from t...  \n",
            "15                   Released in Japan and PAL regions only ; sports and party game  \n",
            "16                                                               Japan-only release  \n",
            "17                                        Realistic re-envisioning of the character  \n",
            "18                                     A Bomberman Game based on the anime Stitch !  \n",
            "19                                               Puzzle game , similar to Bejeweled  },\n",
            "    {   'answer': '2010',\n",
            "        'context':    Year                               Journalists  \\\n",
            "0  2010  Dwayne Grant ( Gold Coast Publications )   \n",
            "1  2011               Leanne West ( Network Ten )   \n",
            "2  2012          Stathi Paxinos ( Fairfax Media )   \n",
            "3  2013              Mike Dalton ( Nine Network )   \n",
            "4  2014    Emma Greenwood ( Gold Coast Bulletin )   \n",
            "5  2015   Amanda Shalala ( ABC Radio Grandstand )   \n",
            "6  2016                             Seven Network   \n",
            "7  2017       Jim Callinan ( Sky News Australia )   \n",
            "8  2018         Matt Carmichael ( Seven Network )   \n",
            "9  2019       Australian Broadcasting Corporation   \n",
            "\n",
            "                                           Story Title  \n",
            "0                                      Never Say Never  \n",
            "1                                   David and Michelle  \n",
            "2                              London Paralympic Games  \n",
            "3                        Special Olympics Junior Games  \n",
            "4                                   He who dares lives  \n",
            "5                       Grandstand para-sport profiles  \n",
            "6                        ' Rio 2016 Paralympic Games '  \n",
            "7                    Oz Day 10K Wheelchair Road Race '  \n",
            "8  2018 Winter Paralympics and 2018 Commonwealth Games  \n",
            "9                                  2018 Invictus Games  },\n",
            "    {   'answer': 'January 31',\n",
            "        'context':         Release                               Title           System  \\\n",
            "0    January 25                     Guardian Heroes              Sat   \n",
            "1    January 26       Mystaria : The Realms of Lore              Sat   \n",
            "2    January 29                       Duke Nukem 3D              DOS   \n",
            "3    January 31                         Mega Man X3             SNES   \n",
            "4    February 9                      Bahamut Lagoon             SNES   \n",
            "5   February 23          Front Mission : Gun Hazard             SNES   \n",
            "6   February 27               Pokémon Red and Green               GB   \n",
            "7   February 29                     Civilization II              Win   \n",
            "8   February 29               Ripper ( video game )              DOS   \n",
            "9   February 29               Rise 2 : Resurrection  Win , Sat , PS1   \n",
            "10  February 29  Terra Nova : Strike Force Centauri              DOS   \n",
            "11  February 29                      Zork : Nemesis              Win   \n",
            "12      March 9                     Super Mario RPG             SNES   \n",
            "13     March 21                    Kirby Super Star             SNES   \n",
            "14     March 22                       Resident Evil              PS1   \n",
            "15     March 22              Panzer Dragoon II Zwei              Sat   \n",
            "16     March 29     Dragon Ball Z : Hyper Dimension             SNES   \n",
            "17     April 20             Barbie Fashion Designer              Win   \n",
            "18     April 26                   Jumping Flash ! 2              PS1   \n",
            "19     April 26                 The Legend of Oasis              Sat   \n",
            "\n",
            "            Developer / Publisher  \\\n",
            "0                 Treasure / Sega   \n",
            "1              Micro Cabin / Sega   \n",
            "2      3D Realms / GT Interactive   \n",
            "3                          Capcom   \n",
            "4                      SquareSoft   \n",
            "5                      SquareSoft   \n",
            "6                        Nintendo   \n",
            "7                      MicroProse   \n",
            "8            Take Two Interactive   \n",
            "9                Mirage / Acclaim   \n",
            "10          Looking Glass Studios   \n",
            "11                     Activision   \n",
            "12            SquareSoft/Nintendo   \n",
            "13            HAL Labs / Nintendo   \n",
            "14                         Capcom   \n",
            "15          Team Andromeda / Sega   \n",
            "16                  TOSE / Bandai   \n",
            "17  Digital Domain / Mattel Media   \n",
            "18                   Exact / SCEA   \n",
            "19                 Sega / Ancient   \n",
            "\n",
            "                                                                              Notes  \n",
            "0                                           a beat-em-up game developed by Treasure  \n",
            "1                                                                    a tactical RPG  \n",
            "2                                                    a popular first person shooter  \n",
            "3                                 third X installment in popular Mega Man franchise  \n",
            "4   Tactical RPG spin-off in the Final Fantasy series , before Final Fantasy Tac...  \n",
            "5                                Sequel to strategy Super Famicom RPG Front Mission  \n",
            "6                                             launched a wildly popular game series  \n",
            "7                           acclaimed sequel to the highly influential 1991 4X game  \n",
            "8                  Interactive movie , Point-and-click adventure Single Player game  \n",
            "9                              the sequel to the fighting game , Rise of the Robots  \n",
            "10                                                         critically acclaimed FPS  \n",
            "11         11th game in the Zork series , employing 360-degree views of environment  \n",
            "12                               beginning of the long-running series of Mario RPGs  \n",
            "13                    considered to be one of the best games in the Kirby franchise  \n",
            "14  one of the foundational games in the survival horror genre , for a time it h...  \n",
            "15                                                        an acclaimed rail shooter  \n",
            "16                       the last Super Famicom game in the Dragon Ball Z franchise  \n",
            "17  The game 's strong sales sparked a renewed interest in developing games targ...  \n",
            "18                                           Sequel to the first true 3D platformer  \n",
            "19                      Prequel to the Genesis Zelda-style action game Beyond Oasis  },\n",
            "    {   'answer': '2009',\n",
            "        'context':                            Song Title    Album ( s ) / Single ( s )  \\\n",
            "0                      A Feast For Me               Pipes & Flowers   \n",
            "1                  A Little Over Zero      Asile 's World / Dancing   \n",
            "2                            A Prayer                         Lotus   \n",
            "3        Anche Se Non Trovi Le Parole                         Heart   \n",
            "4                      And All I Need                         Heart   \n",
            "5                      Asile 's World                Asile 's World   \n",
            "6                     Beautiful Night                         Lotus   \n",
            "7                        Bitter Words                    Pearl Days   \n",
            "8                              Broken               Lotus / Dancing   \n",
            "9                           Chameleon                Asile 's World   \n",
            "10                        City Lights          Pearl Days / Dancing   \n",
            "11                       Coincidences                         Heart   \n",
            "12                         Come & Sit                Asile 's World   \n",
            "13                   Come Speak To Me                Asile 's World   \n",
            "14                           Creature                Asile 's World   \n",
            "15                            Cure Me               Pipes & Flowers   \n",
            "16                            Dancing  Then Comes the Sun / Dancing   \n",
            "17                Dot in the Universe                         Heart   \n",
            "18  Eppure sentire ( Un senso di te )            Soundtrack '96-'06   \n",
            "19                        Electricity                         Lotus   \n",
            "\n",
            "   First Released  \n",
            "0            2002  \n",
            "1            2000  \n",
            "2            2003  \n",
            "3            2009  \n",
            "4            2009  \n",
            "5            2000  \n",
            "6            2003  \n",
            "7            2004  \n",
            "8            2003  \n",
            "9            2000  \n",
            "10           2004  \n",
            "11           2009  \n",
            "12           2000  \n",
            "13           2001  \n",
            "14           2000  \n",
            "15           1997  \n",
            "16           2002  \n",
            "17           2009  \n",
            "18           2006  \n",
            "19           2003  },\n",
            "    {   'answer': 'Windows:NA: October 17, 2006 EU: October 20, 2006 Mac OS '\n",
            "                  'X:November 6, 2006',\n",
            "        'context':                 Name  \\\n",
            "0         University   \n",
            "1          Nightlife   \n",
            "2  Open for Business   \n",
            "3               Pets   \n",
            "4            Seasons   \n",
            "5         Bon Voyage   \n",
            "6           FreeTime   \n",
            "7     Apartment Life   \n",
            "\n",
            "                                                                     Release date  \\\n",
            "0          Windows:NA: March 1, 2005 EU: March 2, 2005 Mac OS X:December 12, 2005   \n",
            "1   Windows:NA: September 13, 2005 EU: September 13, 2005 Mac OS X:March 27, 2006   \n",
            "2          Windows:NA: March 2, 2006 EU: March 2, 2006 Mac OS X:September 4, 2006   \n",
            "3     Windows:NA: October 17, 2006 EU: October 20, 2006 Mac OS X:November 6, 2006   \n",
            "4              Windows:NA: March 1, 2007 EU: March 2, 2007 Mac OS X:June 11, 2007   \n",
            "5  Windows:NA: September 4, 2007 EU: September 7, 2007 Mac OS X:December 17, 2007   \n",
            "6                             Windows:NA: February 26, 2008 EU: February 22, 2008   \n",
            "7                                  Windows:NA: August 27, 2008EU: August 29, 2008   \n",
            "\n",
            "                                                                   Major Additions  \\\n",
            "0                            Universities, Young Adult age group, Influence system   \n",
            "1  Dates, Groups system, Outings, Pleasure and Grilled Cheese aspiration, New r...   \n",
            "2                                                        Businesses, talent badges   \n",
            "3                                                                     Ownable Pets   \n",
            "4                    Weather system, Seasons, fishing, new talent badges,gardening   \n",
            "5                                            Vacations in different cultural areas   \n",
            "6                     Hobby system, lifetime aspiration system, new talent badges.   \n",
            "7                        Rentable apartments, reputation system, witchcraft system   \n",
            "\n",
            "                                                 Neighborhoods  \\\n",
            "0  Campus:La Fiesta Tech,Sim State University,Académie Le Tour   \n",
            "1                                            Downtown:Downtown   \n",
            "2                          Shopping District:Bluewater Village   \n",
            "3                                                         None   \n",
            "4                                      Main:Riverblossom Hills   \n",
            "5         Vacation:Twikkii Island,Three Lakes,Takemizu Village   \n",
            "6                         Main: Desiderata Valley Secret:Hobby   \n",
            "7             Main:Belladonna Cove[53]Secret:The Magical World   \n",
            "\n",
            "                                                                          New NPCs  \\\n",
            "0  Barista, Bartender,Cafeteria Worker,Cheerleader,Coach, Evil Mascot, Mascot,P...   \n",
            "1  Gypsy Matchmaker,Waiter, Chef,Bartender, DJ,Mrs. Crumplebottom,Vampires (Cou...   \n",
            "2                                                                Reporters,Barbers   \n",
            "3                         Animal Control Officers,Obedience Trainer,Wolves, Skunks   \n",
            "4                                                     Garden Club Members,Penguins   \n",
            "5  Fire Dancers,Hotel Maids,Bellboys, Masseurs,Wise Old Man,Pirate, Tour Guides...   \n",
            "6                          Hobby Members,Rod Humble,Hobby Leaders,Food Judge,Genie   \n",
            "7  Butler, Landlord,Roomies,Breakdancers,Street Performers,Social Group Sims,Hi...   \n",
            "\n",
            "                          New Lifestate/Creature  \\\n",
            "0  Zombies (Also in FreeTime and Apartment Life)   \n",
            "1                                       Vampires   \n",
            "2                                Servos (Robots)   \n",
            "3                                     Werewolves   \n",
            "4                                      PlantSims   \n",
            "5                                        Bigfoot   \n",
            "6                               Genie (Only NPC)   \n",
            "7                              Witches, Warlocks   \n",
            "\n",
            "                                                  New Careers  \n",
            "0         Natural Scientist, Paranormal,Show Business, Artist  \n",
            "1                                                        None  \n",
            "2                                              Shop Employees  \n",
            "3                        Pet careers:Security,Showbiz,Service  \n",
            "4            Adventurer,Education,Gamer,Journalism,Law, Music  \n",
            "5                                                        None  \n",
            "6  Oceanography,Intelligence,Entertainment,Dance,Architecture  \n",
            "7                                                        None  },\n",
            "    {   'answer': '2 December 1978',\n",
            "        'context':                                       Album  \\\n",
            "0                          Please Please Me   \n",
            "1                          With the Beatles   \n",
            "2                       A Hard Day 's Night   \n",
            "3                          Beatles for Sale   \n",
            "4                                    Help !   \n",
            "5                               Rubber Soul   \n",
            "6                                  Revolver   \n",
            "7   Sgt . Pepper 's Lonely Hearts Club Band   \n",
            "8               The Beatles ( White Album )   \n",
            "9                          Yellow Submarine   \n",
            "10                               Abbey Road   \n",
            "11                                Let It Be   \n",
            "12                                 Rarities   \n",
            "\n",
            "                                                                              Label  \\\n",
            "0                                                       Parlophone Records PCS 3042   \n",
            "1                                                       Parlophone Records PCS 3045   \n",
            "2                                                       Parlophone Records PCS 3058   \n",
            "3                                                       Parlophone Records PCS 3062   \n",
            "4                                                       Parlophone Records PCS 3071   \n",
            "5                                                       Parlophone Records PCS 3075   \n",
            "6                                                       Parlophone Records PCS 7009   \n",
            "7                                                       Parlophone Records PCS 7027   \n",
            "8                                                          Apple Records PCS 7067/8   \n",
            "9                                                            Apple Records PCS 7070   \n",
            "10                                                           Apple Records PCS 7088   \n",
            "11                                                           Apple Records PCS 7096   \n",
            "12  Parlophone Records PSLP 261 ( British editions ) Capitol SPRO-8969 ( US edit...   \n",
            "\n",
            "         Release date  \n",
            "0       22 March 1963  \n",
            "1    22 November 1963  \n",
            "2        10 July 1964  \n",
            "3     4 December 1964  \n",
            "4       6 August 1965  \n",
            "5     3 December 1965  \n",
            "6       5 August 1966  \n",
            "7         1 June 1967  \n",
            "8    22 November 1968  \n",
            "9     17 January 1969  \n",
            "10  26 September 1969  \n",
            "11         8 May 1970  \n",
            "12    2 December 1978  },\n",
            "    {   'answer': '2 December 1978',\n",
            "        'context':                                       Album  \\\n",
            "0                          Please Please Me   \n",
            "1                          With the Beatles   \n",
            "2                       A Hard Day 's Night   \n",
            "3                          Beatles for Sale   \n",
            "4                                    Help !   \n",
            "5                               Rubber Soul   \n",
            "6                                  Revolver   \n",
            "7   Sgt . Pepper 's Lonely Hearts Club Band   \n",
            "8               The Beatles ( White Album )   \n",
            "9                          Yellow Submarine   \n",
            "10                               Abbey Road   \n",
            "11                                Let It Be   \n",
            "12                                 Rarities   \n",
            "\n",
            "                                                                              Label  \\\n",
            "0                                                       Parlophone Records PCS 3042   \n",
            "1                                                       Parlophone Records PCS 3045   \n",
            "2                                                       Parlophone Records PCS 3058   \n",
            "3                                                       Parlophone Records PCS 3062   \n",
            "4                                                       Parlophone Records PCS 3071   \n",
            "5                                                       Parlophone Records PCS 3075   \n",
            "6                                                       Parlophone Records PCS 7009   \n",
            "7                                                       Parlophone Records PCS 7027   \n",
            "8                                                          Apple Records PCS 7067/8   \n",
            "9                                                            Apple Records PCS 7070   \n",
            "10                                                           Apple Records PCS 7088   \n",
            "11                                                           Apple Records PCS 7096   \n",
            "12  Parlophone Records PSLP 261 ( British editions ) Capitol SPRO-8969 ( US edit...   \n",
            "\n",
            "         Release date  \n",
            "0       22 March 1963  \n",
            "1    22 November 1963  \n",
            "2        10 July 1964  \n",
            "3     4 December 1964  \n",
            "4       6 August 1965  \n",
            "5     3 December 1965  \n",
            "6       5 August 1966  \n",
            "7         1 June 1967  \n",
            "8    22 November 1968  \n",
            "9     17 January 1969  \n",
            "10  26 September 1969  \n",
            "11         8 May 1970  \n",
            "12    2 December 1978  },\n",
            "    {   'answer': 'October22,2004',\n",
            "        'context':    Series # Season #                           Title             Directed by  \\\n",
            "0        44        1  Psychic Eye for the Sloppy Guy            Rich Correll   \n",
            "1        45        2                 Stark Raven Mad             Marc Warren   \n",
            "2        46        3              Opportunity Shocks            Rich Correll   \n",
            "3        47        4           Taken to the Cleaners            Rich Correll   \n",
            "4        48        5            Five Finger Discount            Rich Correll   \n",
            "5        49        6                          Sweeps           Sean McNamara   \n",
            "6        50        7                   Double Vision  T'Keyah Crystal Keymáh   \n",
            "7        51        8             Bend It Like Baxter            Rich Correll   \n",
            "8        52        9                    The Big Buzz        Eric Dean Seaton   \n",
            "9        53       10                     True Colors  Christopher B. Pearman   \n",
            "10       54       11              Dog Day Aftergroom      KC Lynn De Stefano   \n",
            "11       55       12                 Royal Treatment  Christopher B. Pearman   \n",
            "12       56       13                     Art Breaker          Gregory Hobson   \n",
            "13       57       14               Boyz 'N Commotion            Debbie Allen   \n",
            "14       58       15             Gettin' Outta Dodge            Rich Correll   \n",
            "15       59       16             On Top of Old Oakey              John Tracy   \n",
            "16       60       17    They Work Hard for His Honey        Eric Dean Seaton   \n",
            "17       61       18          Mind Your Own Business        Eric Dean Seaton   \n",
            "18       62       19                  Hizzouse Party            Rich Correll   \n",
            "19       63       20                  Mismatch Maker             Fred Savage   \n",
            "20       65       22                    When in Dome             Marc Warren   \n",
            "21       66       23               Too Much Pressure            Rich Correll   \n",
            "22       67       24                    Extreme Cory            Rich Correll   \n",
            "23       68       25             The Grill Next Door           Sean McNamara   \n",
            "24       69       26              Point of No Return           Sean McNamara   \n",
            "25       72       29                Food for Thought            Rich Correll   \n",
            "26       73       30                     Mr. Perfect            Rich Correll   \n",
            "27       74       31                 Goin' Hollywood            Rich Correll   \n",
            "28       75       32             Save the Last Dance           Sean McNamara   \n",
            "29       76       33                       Cake Fear        Rondell Sheridan   \n",
            "30       77       34               Vision Impossible             Marc Warren   \n",
            "\n",
            "                                  Written by Original air date Prod. code  \\\n",
            "0                                Marc Warren     October1,2004        301   \n",
            "1   Sarah Jane Cunningham & Suzie V. Freeman    October22,2004        304   \n",
            "2                                 Dava Savel    November5,2004        309   \n",
            "3                            Michael Feldman   November19,2004        313   \n",
            "4                             Dennis Rinsler    December3,2004        302   \n",
            "5                             Dennis Rinsler   December11,2004        311   \n",
            "6   Sarah Jane Cunningham & Suzie V. Freeman   December17,2004        318   \n",
            "7                                 Dava Savel     January7,2005        315   \n",
            "8                                Marc Warren    January28,2005        322   \n",
            "9                         Michael Carrington    February4,2005        303   \n",
            "10             Theresa Akana & Stacee Comage   February11,2005        317   \n",
            "11  Sarah Jane Cunningham & Suzie V. Freeman   February18,2005        310   \n",
            "12                  Josh Lynn & Danny Warren   February25,2005        308   \n",
            "13             Theresa Akana & Stacee Comage      March11,2005        306   \n",
            "14                           Edward C. Evans       April8,2005        319   \n",
            "15                           Michael Feldman      April22,2005        305   \n",
            "16                           Edward C. Evans      April29,2005        307   \n",
            "17                            Dennis Rinsler        May13,2005        327   \n",
            "18                        Michael Carrington       June13,2005        312   \n",
            "19                           Edward C. Evans       June14,2005        325   \n",
            "20  Sarah Jane Cunningham & Suzie V. Freeman       June16,2005        328   \n",
            "21                                Dava Savel       June17,2005        323   \n",
            "22             Theresa Akana & Stacee Comage        July8,2005        326   \n",
            "23                           Michael Feldman        July8,2005        324   \n",
            "24                           Edward C. Evans       July23,2005        330   \n",
            "25                               Marc Warren  September18,2005        316   \n",
            "26                        Michael Carrington     October7,2005        329   \n",
            "27              Dennis Rinsler & Marc Warren    November4,2005        333   \n",
            "28                               Marc Warren   November25,2005        334   \n",
            "29             Theresa Akana & Stacee Comage   December16,2005        332   \n",
            "30           David Brookwell & Sean McNamara     January6,2006        335   \n",
            "\n",
            "   U.S. viewers (millions)  \n",
            "0                      4.8  \n",
            "1                      4.5  \n",
            "2                      4.5  \n",
            "3                      3.7  \n",
            "4                      3.1  \n",
            "5                      2.6  \n",
            "6                      5.5  \n",
            "7                      4.0  \n",
            "8                     2.17  \n",
            "9                      3.3  \n",
            "10                     2.4  \n",
            "11                     2.7  \n",
            "12                     3.5  \n",
            "13                     4.8  \n",
            "14                     2.1  \n",
            "15                     2.3  \n",
            "16                     4.2  \n",
            "17                     4.4  \n",
            "18                     5.1  \n",
            "19                     4.3  \n",
            "20                     4.7  \n",
            "21                     4.4  \n",
            "22                     3.8  \n",
            "23                    4.23  \n",
            "24                     6.0  \n",
            "25                     3.4  \n",
            "26                     3.0  \n",
            "27                     3.7  \n",
            "28                     3.3  \n",
            "29                     3.6  \n",
            "30                     4.7  },\n",
            "    {   'answer': '1990',\n",
            "        'context':             Year                                                        Title  \\\n",
            "0           1990                                    Psycho IV : The Beginning   \n",
            "1           1992                                          A Taste for Killing   \n",
            "2           1995                              Indictment : The McMartin Trial   \n",
            "3           1996                                    Riders of the Purple Sage   \n",
            "4           1998                                                    Moby Dick   \n",
            "5           1999                                           Happy Face Murders   \n",
            "6           2005                                            Masters of Horror   \n",
            "7           2006                                  Stephen King 's Desperation   \n",
            "8           2006  Nightmares & Dreamscapes : From the Stories of Stephen King   \n",
            "9        2007-08                                              Without a Trace   \n",
            "10          2009                              CSI : Crime Scene Investigation   \n",
            "11          2011                                                The Mentalist   \n",
            "12       2013-14                                                     Betrayal   \n",
            "13          2015                                              Sons of Liberty   \n",
            "14          2016                           Law & Order : Special Victims Unit   \n",
            "15          2017                                                Better Things   \n",
            "16  2018-present                                   The Haunting of Hill House   \n",
            "17          2018                                           Girl in the Bunker   \n",
            "18          2020                                            FBI : Most Wanted   \n",
            "19          2020                                                     Stargirl   \n",
            "\n",
            "                                              Role  \\\n",
            "0                               Young Norman Bates   \n",
            "1                                       Cary Sloan   \n",
            "2                                       Ray Buckey   \n",
            "3                                     Bern Venters   \n",
            "4                                          Ishmael   \n",
            "5                                   Dylan McCarthy   \n",
            "6                                            Jamie   \n",
            "7                                    Peter Jackson   \n",
            "8                                    Robert Fornoy   \n",
            "9                                   Franklin Romar   \n",
            "10                                     Jeremy Kent   \n",
            "11                                   Thomas Lisbon   \n",
            "12                                    T.J. Karsten   \n",
            "13                                      John Adams   \n",
            "14                                    Sean Roberts   \n",
            "15                                           Robin   \n",
            "16  Young Hugh Crain ( season 1 ) TBA ( season 2 )   \n",
            "17                                   Vinson Filyaw   \n",
            "18                                Dr. Justin Brock   \n",
            "19               Charles McNider / Doctor Mid-Nite   \n",
            "\n",
            "                                                Notes  \n",
            "0                                     Television film  \n",
            "1                                     Television film  \n",
            "2                                     Television film  \n",
            "3                                     Television film  \n",
            "4                                          Miniseries  \n",
            "5                                     Television film  \n",
            "6                                 Episode : Chocolate  \n",
            "7                                     Television film  \n",
            "8                 Episode : The End of the Whole Mess  \n",
            "9                                          2 episodes  \n",
            "10                        Episode : If I Had a Hammer  \n",
            "11  Episode : Where in the World is Carmine O'Brien ?  \n",
            "12                                        13 episodes  \n",
            "13                                         Miniseries  \n",
            "14                          Episode : Making a Rapist  \n",
            "15                                         4 episodes  \n",
            "16           Series regular , first and second season  \n",
            "17                                    Television film  \n",
            "18                                 Episode : Dopesick  \n",
            "19                                     Recurring role  }]\n"
          ]
        }
      ],
      "source": [
        "prediction = table_qa_pipeline.run(\"When was Guilty Gear Xrd : Sign released?\", params={\"top_k\": 30})\n",
        "print_answers(prediction, details=\"minimum\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "4CBcIjIq_uFx"
      },
      "outputs": [],
      "source": [
        "# Add 500 text passages to our document store.\n",
        "\n",
        "\n",
        "def read_texts(filename):\n",
        "    processed_passages = []\n",
        "    with open(filename) as passages:\n",
        "        passages = json.load(passages)\n",
        "        for key, content in passages.items():\n",
        "            document = Document(content=content, content_type=\"text\", id=key)\n",
        "            processed_passages.append(document)\n",
        "\n",
        "    return processed_passages\n",
        "\n",
        "\n",
        "passages = read_texts(f\"{doc_dir}/texts.json\")\n",
        "document_store.write_documents(passages, index=document_index)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "j1TaNF7SiKgH",
        "outputId": "26b81b70-64f9-4870-bdc5-602c91817b00",
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      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.document_stores.elasticsearch -  Updating embeddings for 563 docs without embeddings ...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Updating embeddings:   0%|          | 0/563 [00:00<?, ? Docs/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "88a5b70764d944e69e4405740fde2a7b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Create embeddings:   0%|          | 0/576 [00:00<?, ? Docs/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
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      ],
      "source": [
        "document_store.update_embeddings(retriever=retriever, update_existing_embeddings=False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c2sk_uNHj0DY"
      },
      "source": [
        "## Pipeline for QA on Combination of Text and Tables\n",
        "We are using one node for retrieving both texts and tables, the `TableTextRetriever`. In order to do question-answering on the Documents coming from the `TableTextRetriever`, we need to route Documents of type `\"text\"` to a `FARMReader` (or alternatively `TransformersReader`) and Documents of type `\"table\"` to a `TableReader`.\n",
        "\n",
        "To achieve this, we make use of two additional nodes:\n",
        "- `RouteDocuments`: Splits the List of Documents retrieved by the `TableTextRetriever` into two lists containing only Documents of type `\"text\"` or `\"table\"`, respectively.\n",
        "- `JoinAnswers`: Takes Answers coming from two different Readers (in this case `FARMReader` and `TableReader`) and joins them to a single list of Answers."
      ]
    },
    {
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        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.utils -  Using devices: CUDA:0\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n",
            "INFO - haystack.modeling.model.language_model -  LOADING MODEL\n",
            "INFO - haystack.modeling.model.language_model -  =============\n",
            "INFO - haystack.modeling.model.language_model -  Could not find deepset/roberta-base-squad2 locally.\n",
            "INFO - haystack.modeling.model.language_model -  Looking on Transformers Model Hub (in local cache and online)...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "88a09b817dd24ff68e360a72ad1a7053"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f326259db5a4407898a886cf6a1a8746"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO - haystack.modeling.model.language_model -  Loaded deepset/roberta-base-squad2\n",
            "WARNING - haystack.modeling.logger -  Failed to log params: Changing param values is not allowed. Param with key='prediction_heads' was already logged with value='TextSimilarityHead' for run ID='74ed0066b5874640b2324fba7521dbb2'. Attempted logging new value 'QuestionAnsweringHead'.\n"
          ]
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "81ed2c7c2b7145f29961c5c01fd6a6ab"
            }
          },
          "metadata": {}
        },
        {
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e6df76d1e5034b9ba4ad2662ea210553"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ee544aa8026c43ce984c6eff62480587"
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          },
          "metadata": {}
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fd845158fd9c456a9c0b115f9960dcda"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING - haystack.modeling.logger -  Failed to log params: Changing param values is not allowed. Param with key='processor' was already logged with value='TableTextSimilarityProcessor' for run ID='74ed0066b5874640b2324fba7521dbb2'. Attempted logging new value 'SquadProcessor'.\n",
            "INFO - haystack.modeling.logger -  ML Logging is turned off. No parameters, metrics or artifacts will be logged to MLFlow.\n",
            "INFO - haystack.modeling.utils -  Using devices: CUDA\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n",
            "INFO - haystack.modeling.infer -  Got ya 2 parallel workers to do inference ...\n",
            "INFO - haystack.modeling.infer -   0     0  \n",
            "INFO - haystack.modeling.infer -  /w\\   /w\\ \n",
            "INFO - haystack.modeling.infer -  /'\\   / \\ \n",
            "WARNING - haystack.nodes.base -  Unnamed __init__ parameters will not be saved to YAML if Pipeline.save_to_yaml() is called!\n",
            "INFO - haystack.modeling.utils -  Using devices: CUDA\n",
            "INFO - haystack.modeling.utils -  Number of GPUs: 1\n"
          ]
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5f85912142ad4600be0ca9322184676a"
            }
          },
          "metadata": {}
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3b0c1a281e9e4e49a43a80a6b915ec38"
            }
          },
          "metadata": {}
        },
        {
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d061edb888ab4e8fa883f84274fd0847"
            }
          },
          "metadata": {}
        },
        {
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ad874e85d6414d218d3693608e7740eb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "10d2e7a4feb6454cb29a499081f148fb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING - haystack.nodes.base -  Unnamed __init__ parameters will not be saved to YAML if Pipeline.save_to_yaml() is called!\n"
          ]
        }
      ],
      "source": [
        "from haystack.nodes import FARMReader, RouteDocuments, JoinAnswers\n",
        "\n",
        "text_reader = FARMReader(\"deepset/roberta-base-squad2\")\n",
        "# In order to get meaningful scores from the TableReader, use \"deepset/tapas-large-nq-hn-reader\" or\n",
        "# \"deepset/tapas-large-nq-reader\" as TableReader models. The disadvantage of these models is, however,\n",
        "# that they are not capable of doing aggregations over multiple table cells.\n",
        "table_reader = TableReader(\"deepset/tapas-large-nq-hn-reader\")\n",
        "route_documents = RouteDocuments()\n",
        "join_answers = JoinAnswers()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "Zdq6JnF5m3aP"
      },
      "outputs": [],
      "source": [
        "text_table_qa_pipeline = Pipeline()\n",
        "text_table_qa_pipeline.add_node(component=retriever, name=\"TableTextRetriever\", inputs=[\"Query\"])\n",
        "text_table_qa_pipeline.add_node(component=route_documents, name=\"RouteDocuments\", inputs=[\"TableTextRetriever\"])\n",
        "text_table_qa_pipeline.add_node(component=text_reader, name=\"TextReader\", inputs=[\"RouteDocuments.output_1\"])\n",
        "text_table_qa_pipeline.add_node(component=table_reader, name=\"TableReader\", inputs=[\"RouteDocuments.output_2\"])\n",
        "text_table_qa_pipeline.add_node(component=join_answers, name=\"JoinAnswers\", inputs=[\"TextReader\", \"TableReader\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 540
        },
        "id": "K4vH1ZEnniut",
        "outputId": "4a910edb-10bf-44ff-da88-5fbaec8a4952"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "# Let's have a look on the structure of the combined Table an Text QA pipeline.\n",
        "from IPython import display\n",
        "\n",
        "text_table_qa_pipeline.draw()\n",
        "display.Image(\"pipeline.png\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "strPNduPoBLe",
        "outputId": "ef0bd2e9-ab97-4a69-a286-4c33d84f32e0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Inferencing Samples:   0%|          | 0/1 [00:00<?, ? Batches/s]/usr/local/lib/python3.7/dist-packages/haystack/modeling/model/prediction_head.py:478: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
            "  start_indices = flat_sorted_indices // max_seq_len\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  8.29 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 15.50 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 15.55 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 15.62 Batches/s]\n"
          ]
        }
      ],
      "source": [
        "# Example query whose answer resides in a text passage\n",
        "predictions = text_table_qa_pipeline.run(query=\"Who was Thomas Alva Edison?\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9YiK75tSoOGA",
        "outputId": "1136da0f-ea43-4aaf-d6a0-59fb3c20c16a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: Who was Thomas Alva Edison?\n",
            "Answers:\n",
            "[   {   'answer': 'American inventor and businessman',\n",
            "        'context': 'mas Alva Edison (February 11, 1847October 18, 1931) was an '\n",
            "                   'American inventor and businessman, who has been described '\n",
            "                   \"as America's greatest inventor. H\"},\n",
            "    {   'answer': 'Dorothy Colpoys',\n",
            "        'context':     Year       Men's singles   Women's singles  \\\n",
            "0   1928      Alan Titherley          R. Finch   \n",
            "1   1929          T. P. Dick  Margaret Tragett   \n",
            "2   1930         Donald Hume   Dorothy Colpoys   \n",
            "3   1931          T. P. Dick   Dorothy Colpoys   \n",
            "4   1932         W. Hamilton  Thelma Kingsbury   \n",
            "..   ...                 ...               ...   \n",
            "59  2008      Brice Leverdez      Kati Tolmoff   \n",
            "60  2009    Kristian Nielsen     Tatjana Bibik   \n",
            "61  2010         Pablo Abián    Anita Raj Kaur   \n",
            "62  2011  Niluka Karunaratne   Nicole Schaller   \n",
            "63  2012      Chou Tien-chen    Chiang Mei-hui   \n",
            "\n",
            "                         Men's doubles                       Women's doubles  \\\n",
            "0     J. D. M. McCallum Alan Titherley                   Thompson-Smith Reid   \n",
            "1       F. J. Treasure F. B. Malthouse            Marian Horsley L. W. Myers   \n",
            "2            Donald Hume Ralph Nichols            Marian Horsley L. W. Myers   \n",
            "3            T. P. Dick W. Basil Jones            Marian Horsley L. W. Myers   \n",
            "4           Artur Hamilton W. Hamilton        Hazel Hogarth Thelma Kingsbury   \n",
            "..                                 ...                                   ...   \n",
            "59          Andrew Bowman Martyn Lewis    Mariana Agathangelou Jillie Cooper   \n",
            "60  Vitaliy Durkin Alexandr Nikolaenko         Valeria Sorokina Nina Vislova   \n",
            "61      Peter Käsbauer Josche Zurwonne  Joanne Quay Swee Ling Anita Raj Kaur   \n",
            "62      Chris Coles Matthew Nottingham                 Ng Hui Ern Ng Hui Lin   \n",
            "63     Marcus Ellis Paul Van Rietvelde          Gabrielle White Lauren Smith   \n",
            "\n",
            "                         Mixed doubles  \n",
            "0              F. L. Treasure Meredith  \n",
            "1             T. P. Dick Hazel Hogarth  \n",
            "2             T. P. Dick Hazel Hogarth  \n",
            "3             T. P. Dick Hazel Hogarth  \n",
            "4                Ralph Nichols N. Coop  \n",
            "..                                 ...  \n",
            "59         Watson Briggs Jillie Cooper  \n",
            "60         Vitaliy Durkin Nina Vislova  \n",
            "61  Peter Käsbauer Johanna Goliszewski  \n",
            "62          Martin Campbell Ng Hui Lin  \n",
            "63        Marcus Ellis Gabrielle White  \n",
            "\n",
            "[64 rows x 6 columns]},\n",
            "    {   'answer': 'Daphne Young',\n",
            "        'context':     Year       Men's singles   Women's singles  \\\n",
            "0   1928      Alan Titherley          R. Finch   \n",
            "1   1929          T. P. Dick  Margaret Tragett   \n",
            "2   1930         Donald Hume   Dorothy Colpoys   \n",
            "3   1931          T. P. Dick   Dorothy Colpoys   \n",
            "4   1932         W. Hamilton  Thelma Kingsbury   \n",
            "..   ...                 ...               ...   \n",
            "59  2008      Brice Leverdez      Kati Tolmoff   \n",
            "60  2009    Kristian Nielsen     Tatjana Bibik   \n",
            "61  2010         Pablo Abián    Anita Raj Kaur   \n",
            "62  2011  Niluka Karunaratne   Nicole Schaller   \n",
            "63  2012      Chou Tien-chen    Chiang Mei-hui   \n",
            "\n",
            "                         Men's doubles                       Women's doubles  \\\n",
            "0     J. D. M. McCallum Alan Titherley                   Thompson-Smith Reid   \n",
            "1       F. J. Treasure F. B. Malthouse            Marian Horsley L. W. Myers   \n",
            "2            Donald Hume Ralph Nichols            Marian Horsley L. W. Myers   \n",
            "3            T. P. Dick W. Basil Jones            Marian Horsley L. W. Myers   \n",
            "4           Artur Hamilton W. Hamilton        Hazel Hogarth Thelma Kingsbury   \n",
            "..                                 ...                                   ...   \n",
            "59          Andrew Bowman Martyn Lewis    Mariana Agathangelou Jillie Cooper   \n",
            "60  Vitaliy Durkin Alexandr Nikolaenko         Valeria Sorokina Nina Vislova   \n",
            "61      Peter Käsbauer Josche Zurwonne  Joanne Quay Swee Ling Anita Raj Kaur   \n",
            "62      Chris Coles Matthew Nottingham                 Ng Hui Ern Ng Hui Lin   \n",
            "63     Marcus Ellis Paul Van Rietvelde          Gabrielle White Lauren Smith   \n",
            "\n",
            "                         Mixed doubles  \n",
            "0              F. L. Treasure Meredith  \n",
            "1             T. P. Dick Hazel Hogarth  \n",
            "2             T. P. Dick Hazel Hogarth  \n",
            "3             T. P. Dick Hazel Hogarth  \n",
            "4                Ralph Nichols N. Coop  \n",
            "..                                 ...  \n",
            "59         Watson Briggs Jillie Cooper  \n",
            "60         Vitaliy Durkin Nina Vislova  \n",
            "61  Peter Käsbauer Johanna Goliszewski  \n",
            "62          Martin Campbell Ng Hui Lin  \n",
            "63        Marcus Ellis Gabrielle White  \n",
            "\n",
            "[64 rows x 6 columns]},\n",
            "    {   'answer': 'Maggie McIntosh',\n",
            "        'context':     Year       Men's singles   Women's singles  \\\n",
            "0   1928      Alan Titherley          R. Finch   \n",
            "1   1929          T. P. Dick  Margaret Tragett   \n",
            "2   1930         Donald Hume   Dorothy Colpoys   \n",
            "3   1931          T. P. Dick   Dorothy Colpoys   \n",
            "4   1932         W. Hamilton  Thelma Kingsbury   \n",
            "..   ...                 ...               ...   \n",
            "59  2008      Brice Leverdez      Kati Tolmoff   \n",
            "60  2009    Kristian Nielsen     Tatjana Bibik   \n",
            "61  2010         Pablo Abián    Anita Raj Kaur   \n",
            "62  2011  Niluka Karunaratne   Nicole Schaller   \n",
            "63  2012      Chou Tien-chen    Chiang Mei-hui   \n",
            "\n",
            "                         Men's doubles                       Women's doubles  \\\n",
            "0     J. D. M. McCallum Alan Titherley                   Thompson-Smith Reid   \n",
            "1       F. J. Treasure F. B. Malthouse            Marian Horsley L. W. Myers   \n",
            "2            Donald Hume Ralph Nichols            Marian Horsley L. W. Myers   \n",
            "3            T. P. Dick W. Basil Jones            Marian Horsley L. W. Myers   \n",
            "4           Artur Hamilton W. Hamilton        Hazel Hogarth Thelma Kingsbury   \n",
            "..                                 ...                                   ...   \n",
            "59          Andrew Bowman Martyn Lewis    Mariana Agathangelou Jillie Cooper   \n",
            "60  Vitaliy Durkin Alexandr Nikolaenko         Valeria Sorokina Nina Vislova   \n",
            "61      Peter Käsbauer Josche Zurwonne  Joanne Quay Swee Ling Anita Raj Kaur   \n",
            "62      Chris Coles Matthew Nottingham                 Ng Hui Ern Ng Hui Lin   \n",
            "63     Marcus Ellis Paul Van Rietvelde          Gabrielle White Lauren Smith   \n",
            "\n",
            "                         Mixed doubles  \n",
            "0              F. L. Treasure Meredith  \n",
            "1             T. P. Dick Hazel Hogarth  \n",
            "2             T. P. Dick Hazel Hogarth  \n",
            "3             T. P. Dick Hazel Hogarth  \n",
            "4                Ralph Nichols N. Coop  \n",
            "..                                 ...  \n",
            "59         Watson Briggs Jillie Cooper  \n",
            "60         Vitaliy Durkin Nina Vislova  \n",
            "61  Peter Käsbauer Johanna Goliszewski  \n",
            "62          Martin Campbell Ng Hui Lin  \n",
            "63        Marcus Ellis Gabrielle White  \n",
            "\n",
            "[64 rows x 6 columns]},\n",
            "    {   'answer': '1947',\n",
            "        'context':     Year  \\\n",
            "0   1947   \n",
            "1   1951   \n",
            "2   1952   \n",
            "3   1959   \n",
            "4   1960   \n",
            "5   1964   \n",
            "6   1970   \n",
            "7   1976   \n",
            "8   1976   \n",
            "9   1986   \n",
            "10  1986   \n",
            "11  1987   \n",
            "12  2001   \n",
            "13  2008   \n",
            "14  2013   \n",
            "\n",
            "                                  Cast ( Macbeth , Lady Macbeth , Macduff , Banco )  \\\n",
            "0             Francesco Valentino , Margherita Grandi , Walter Midgley , Italo Tajo   \n",
            "1                            Ivan Petroff , Astrid Varnay , Gino Penno , Italo Tajo   \n",
            "2                          Enzo Mascherini , Maria Callas , Gino Penno , Italo Tajo   \n",
            "3                   Leonard Warren , Leonie Rysanek , Carlo Bergonzi , Jerome Hines   \n",
            "4                  Giuseppe Taddei , Leyla Gencer , Mirto Picchi , Ferrucio Mazzoli   \n",
            "5                Giuseppe Taddei , Birgit Nilsson , Bruno Prevedi , Giovanni Foiani   \n",
            "6   Dietrich Fischer-Dieskau , Elena Souliotis , Luciano Pavarotti , Nicolai Ghi...   \n",
            "7          Piero Cappuccilli , Shirley Verrett , Plácido Domingo , Nicolai Ghiaurov   \n",
            "8            Sherrill Milnes , Fiorenza Cossotto , José Carreras , Ruggero Raimondi   \n",
            "9                     Leo Nucci , Shirley Verrett , Veriano Luchetti , Samuel Ramey   \n",
            "10       Piero Cappuccilli , Sylvia Sass , Péter Kelen [ hu ] , Kolos Kováts [ hu ]   \n",
            "11                      Renato Bruson , Mara Zampieri , Neil Shicoff , Robert Lloyd   \n",
            "12               Thomas Hampson , Paoletta Marrocu , Luis Lima , Roberto Scandiuzzi   \n",
            "13                    Željko Lučić , Maria Guleghina , John Relyea , Dimitri Pittas   \n",
            "14                       Leo Nucci , Sylvie Valayre , Enrico Iori , Roberto Iuliano   \n",
            "\n",
            "                                              Conductor , opera house and orchestra  \\\n",
            "0   Berthold Goldschmidt Scottish Orchestra , Glyndebourne Festival Chorus ( Liv...   \n",
            "1   Vittorio Gui Chorus and Orchestra of the Teatro Communale di Firenze ( Live ...   \n",
            "2   Victor de Sabata La Scala Chorus and Orchestra ( Live recording of 7 Dec. pe...   \n",
            "3                           Erich Leinsdorf Metropolitan Opera Chorus and Orchestra   \n",
            "4                                  Vittorio Gui Teatro Massimo Chorus and Orchestra   \n",
            "5                Thomas Schippers , Accademia di Santa Cecilia Orchestra and Chorus   \n",
            "6      Lamberto Gardelli , London Philharmonic Orchestra and Ambrosian Opera Chorus   \n",
            "7                           Claudio Abbado , Coro e Orchestra del Teatro alla Scala   \n",
            "8             Riccardo Muti , New Philharmonia Orchestra and Ambrosian Opera Chorus   \n",
            "9                Riccardo Chailly , Teatro Comunale di Bologna Orchestra and Chorus   \n",
            "10  Lamberto Gardelli , Hungarian Radio and Television Chorus and Budapest Symph...   \n",
            "11  Giuseppe Sinopoli , Orchester und Chor der Deutsche Oper Berlin ( Live recor...   \n",
            "12  Franz Welser-Möst , Chorus and Orchestra of the Zürich Opera House ( Live re...   \n",
            "13  James Levine , Metropolitan Opera Orchestra , Chorus , and Ballet ( Live rec...   \n",
            "14  Bruno Bartoletti , Teatro Regio di Parma ( 2006 production ) Drected by Lili...   \n",
            "\n",
            "                                                                         Label  \n",
            "0               CD : Classical Recordings Quarterly Editions Cat : CRQ CD004-5  \n",
            "1                                          Operadepot-dot-com Cat : CD-10939-2  \n",
            "2                                                CD : Myto Cat : MCD 063 H 115  \n",
            "3                                              CD : RCA Victor Cat : 4516-2-RG  \n",
            "4                       CD : Great Opera Performances ( GOP ) Cat : B00HYKI61Y  \n",
            "5                                                   CD : Decca Cat : 433 039-2  \n",
            "6                                                   CD : Decca Cat : 440 048-2  \n",
            "7                                     CD : Deutsche Grammophon Cat : 449 732-2  \n",
            "8                                                 CD : EMI Cat : CMS 5 67128-2  \n",
            "9   CD : Decca Cat : 417 525-2 DVD : Decca , Cat : 073 4380 and 1040309 ( US )  \n",
            "10                                          CD : Hungaroton Cat : HCD 12738-40  \n",
            "11                                           DVD : ArtHaus Musik Cat : 100 141  \n",
            "12                                                    DVD : TDK Cat : DV-OPMAC  \n",
            "13                                            DVD : EMI Classics Cat : 2063049  \n",
            "14                                                  DVD : C Major Cat : 722008  },\n",
            "    {   'answer': 'Victor de Sabata La Scala Chorus and Orchestra ( Live '\n",
            "                  'recording of 7 Dec. performance )',\n",
            "        'context':     Year  \\\n",
            "0   1947   \n",
            "1   1951   \n",
            "2   1952   \n",
            "3   1959   \n",
            "4   1960   \n",
            "5   1964   \n",
            "6   1970   \n",
            "7   1976   \n",
            "8   1976   \n",
            "9   1986   \n",
            "10  1986   \n",
            "11  1987   \n",
            "12  2001   \n",
            "13  2008   \n",
            "14  2013   \n",
            "\n",
            "                                  Cast ( Macbeth , Lady Macbeth , Macduff , Banco )  \\\n",
            "0             Francesco Valentino , Margherita Grandi , Walter Midgley , Italo Tajo   \n",
            "1                            Ivan Petroff , Astrid Varnay , Gino Penno , Italo Tajo   \n",
            "2                          Enzo Mascherini , Maria Callas , Gino Penno , Italo Tajo   \n",
            "3                   Leonard Warren , Leonie Rysanek , Carlo Bergonzi , Jerome Hines   \n",
            "4                  Giuseppe Taddei , Leyla Gencer , Mirto Picchi , Ferrucio Mazzoli   \n",
            "5                Giuseppe Taddei , Birgit Nilsson , Bruno Prevedi , Giovanni Foiani   \n",
            "6   Dietrich Fischer-Dieskau , Elena Souliotis , Luciano Pavarotti , Nicolai Ghi...   \n",
            "7          Piero Cappuccilli , Shirley Verrett , Plácido Domingo , Nicolai Ghiaurov   \n",
            "8            Sherrill Milnes , Fiorenza Cossotto , José Carreras , Ruggero Raimondi   \n",
            "9                     Leo Nucci , Shirley Verrett , Veriano Luchetti , Samuel Ramey   \n",
            "10       Piero Cappuccilli , Sylvia Sass , Péter Kelen [ hu ] , Kolos Kováts [ hu ]   \n",
            "11                      Renato Bruson , Mara Zampieri , Neil Shicoff , Robert Lloyd   \n",
            "12               Thomas Hampson , Paoletta Marrocu , Luis Lima , Roberto Scandiuzzi   \n",
            "13                    Željko Lučić , Maria Guleghina , John Relyea , Dimitri Pittas   \n",
            "14                       Leo Nucci , Sylvie Valayre , Enrico Iori , Roberto Iuliano   \n",
            "\n",
            "                                              Conductor , opera house and orchestra  \\\n",
            "0   Berthold Goldschmidt Scottish Orchestra , Glyndebourne Festival Chorus ( Liv...   \n",
            "1   Vittorio Gui Chorus and Orchestra of the Teatro Communale di Firenze ( Live ...   \n",
            "2   Victor de Sabata La Scala Chorus and Orchestra ( Live recording of 7 Dec. pe...   \n",
            "3                           Erich Leinsdorf Metropolitan Opera Chorus and Orchestra   \n",
            "4                                  Vittorio Gui Teatro Massimo Chorus and Orchestra   \n",
            "5                Thomas Schippers , Accademia di Santa Cecilia Orchestra and Chorus   \n",
            "6      Lamberto Gardelli , London Philharmonic Orchestra and Ambrosian Opera Chorus   \n",
            "7                           Claudio Abbado , Coro e Orchestra del Teatro alla Scala   \n",
            "8             Riccardo Muti , New Philharmonia Orchestra and Ambrosian Opera Chorus   \n",
            "9                Riccardo Chailly , Teatro Comunale di Bologna Orchestra and Chorus   \n",
            "10  Lamberto Gardelli , Hungarian Radio and Television Chorus and Budapest Symph...   \n",
            "11  Giuseppe Sinopoli , Orchester und Chor der Deutsche Oper Berlin ( Live recor...   \n",
            "12  Franz Welser-Möst , Chorus and Orchestra of the Zürich Opera House ( Live re...   \n",
            "13  James Levine , Metropolitan Opera Orchestra , Chorus , and Ballet ( Live rec...   \n",
            "14  Bruno Bartoletti , Teatro Regio di Parma ( 2006 production ) Drected by Lili...   \n",
            "\n",
            "                                                                         Label  \n",
            "0               CD : Classical Recordings Quarterly Editions Cat : CRQ CD004-5  \n",
            "1                                          Operadepot-dot-com Cat : CD-10939-2  \n",
            "2                                                CD : Myto Cat : MCD 063 H 115  \n",
            "3                                              CD : RCA Victor Cat : 4516-2-RG  \n",
            "4                       CD : Great Opera Performances ( GOP ) Cat : B00HYKI61Y  \n",
            "5                                                   CD : Decca Cat : 433 039-2  \n",
            "6                                                   CD : Decca Cat : 440 048-2  \n",
            "7                                     CD : Deutsche Grammophon Cat : 449 732-2  \n",
            "8                                                 CD : EMI Cat : CMS 5 67128-2  \n",
            "9   CD : Decca Cat : 417 525-2 DVD : Decca , Cat : 073 4380 and 1040309 ( US )  \n",
            "10                                          CD : Hungaroton Cat : HCD 12738-40  \n",
            "11                                           DVD : ArtHaus Musik Cat : 100 141  \n",
            "12                                                    DVD : TDK Cat : DV-OPMAC  \n",
            "13                                            DVD : EMI Classics Cat : 2063049  \n",
            "14                                                  DVD : C Major Cat : 722008  },\n",
            "    {   'answer': '1951',\n",
            "        'context':     Year  \\\n",
            "0   1947   \n",
            "1   1951   \n",
            "2   1952   \n",
            "3   1959   \n",
            "4   1960   \n",
            "5   1964   \n",
            "6   1970   \n",
            "7   1976   \n",
            "8   1976   \n",
            "9   1986   \n",
            "10  1986   \n",
            "11  1987   \n",
            "12  2001   \n",
            "13  2008   \n",
            "14  2013   \n",
            "\n",
            "                                  Cast ( Macbeth , Lady Macbeth , Macduff , Banco )  \\\n",
            "0             Francesco Valentino , Margherita Grandi , Walter Midgley , Italo Tajo   \n",
            "1                            Ivan Petroff , Astrid Varnay , Gino Penno , Italo Tajo   \n",
            "2                          Enzo Mascherini , Maria Callas , Gino Penno , Italo Tajo   \n",
            "3                   Leonard Warren , Leonie Rysanek , Carlo Bergonzi , Jerome Hines   \n",
            "4                  Giuseppe Taddei , Leyla Gencer , Mirto Picchi , Ferrucio Mazzoli   \n",
            "5                Giuseppe Taddei , Birgit Nilsson , Bruno Prevedi , Giovanni Foiani   \n",
            "6   Dietrich Fischer-Dieskau , Elena Souliotis , Luciano Pavarotti , Nicolai Ghi...   \n",
            "7          Piero Cappuccilli , Shirley Verrett , Plácido Domingo , Nicolai Ghiaurov   \n",
            "8            Sherrill Milnes , Fiorenza Cossotto , José Carreras , Ruggero Raimondi   \n",
            "9                     Leo Nucci , Shirley Verrett , Veriano Luchetti , Samuel Ramey   \n",
            "10       Piero Cappuccilli , Sylvia Sass , Péter Kelen [ hu ] , Kolos Kováts [ hu ]   \n",
            "11                      Renato Bruson , Mara Zampieri , Neil Shicoff , Robert Lloyd   \n",
            "12               Thomas Hampson , Paoletta Marrocu , Luis Lima , Roberto Scandiuzzi   \n",
            "13                    Željko Lučić , Maria Guleghina , John Relyea , Dimitri Pittas   \n",
            "14                       Leo Nucci , Sylvie Valayre , Enrico Iori , Roberto Iuliano   \n",
            "\n",
            "                                              Conductor , opera house and orchestra  \\\n",
            "0   Berthold Goldschmidt Scottish Orchestra , Glyndebourne Festival Chorus ( Liv...   \n",
            "1   Vittorio Gui Chorus and Orchestra of the Teatro Communale di Firenze ( Live ...   \n",
            "2   Victor de Sabata La Scala Chorus and Orchestra ( Live recording of 7 Dec. pe...   \n",
            "3                           Erich Leinsdorf Metropolitan Opera Chorus and Orchestra   \n",
            "4                                  Vittorio Gui Teatro Massimo Chorus and Orchestra   \n",
            "5                Thomas Schippers , Accademia di Santa Cecilia Orchestra and Chorus   \n",
            "6      Lamberto Gardelli , London Philharmonic Orchestra and Ambrosian Opera Chorus   \n",
            "7                           Claudio Abbado , Coro e Orchestra del Teatro alla Scala   \n",
            "8             Riccardo Muti , New Philharmonia Orchestra and Ambrosian Opera Chorus   \n",
            "9                Riccardo Chailly , Teatro Comunale di Bologna Orchestra and Chorus   \n",
            "10  Lamberto Gardelli , Hungarian Radio and Television Chorus and Budapest Symph...   \n",
            "11  Giuseppe Sinopoli , Orchester und Chor der Deutsche Oper Berlin ( Live recor...   \n",
            "12  Franz Welser-Möst , Chorus and Orchestra of the Zürich Opera House ( Live re...   \n",
            "13  James Levine , Metropolitan Opera Orchestra , Chorus , and Ballet ( Live rec...   \n",
            "14  Bruno Bartoletti , Teatro Regio di Parma ( 2006 production ) Drected by Lili...   \n",
            "\n",
            "                                                                         Label  \n",
            "0               CD : Classical Recordings Quarterly Editions Cat : CRQ CD004-5  \n",
            "1                                          Operadepot-dot-com Cat : CD-10939-2  \n",
            "2                                                CD : Myto Cat : MCD 063 H 115  \n",
            "3                                              CD : RCA Victor Cat : 4516-2-RG  \n",
            "4                       CD : Great Opera Performances ( GOP ) Cat : B00HYKI61Y  \n",
            "5                                                   CD : Decca Cat : 433 039-2  \n",
            "6                                                   CD : Decca Cat : 440 048-2  \n",
            "7                                     CD : Deutsche Grammophon Cat : 449 732-2  \n",
            "8                                                 CD : EMI Cat : CMS 5 67128-2  \n",
            "9   CD : Decca Cat : 417 525-2 DVD : Decca , Cat : 073 4380 and 1040309 ( US )  \n",
            "10                                          CD : Hungaroton Cat : HCD 12738-40  \n",
            "11                                           DVD : ArtHaus Musik Cat : 100 141  \n",
            "12                                                    DVD : TDK Cat : DV-OPMAC  \n",
            "13                                            DVD : EMI Classics Cat : 2063049  \n",
            "14                                                  DVD : C Major Cat : 722008  },\n",
            "    {   'answer': '35.0',\n",
            "        'context':     Rank       Player (2018 HRs)   HR\n",
            "0    1.0             Barry Bonds  762\n",
            "1    2.0            Hank Aaron *  755\n",
            "2    3.0             Babe Ruth *  714\n",
            "3    4.0          Alex Rodriguez  696\n",
            "4    5.0           Willie Mays *  660\n",
            "..   ...                     ...  ...\n",
            "70  71.0  Edwin Encarnación (32)  380\n",
            "71  72.0        Orlando Cepeda *  379\n",
            "72   nan            Tony Pérez *  379\n",
            "73  74.0           Matt Williams  378\n",
            "74  75.0               Norm Cash  377\n",
            "\n",
            "[75 rows x 3 columns]},\n",
            "    {   'answer': 'Barry Bonds',\n",
            "        'context':     Rank       Player (2018 HRs)   HR\n",
            "0    1.0             Barry Bonds  762\n",
            "1    2.0            Hank Aaron *  755\n",
            "2    3.0             Babe Ruth *  714\n",
            "3    4.0          Alex Rodriguez  696\n",
            "4    5.0           Willie Mays *  660\n",
            "..   ...                     ...  ...\n",
            "70  71.0  Edwin Encarnación (32)  380\n",
            "71  72.0        Orlando Cepeda *  379\n",
            "72   nan            Tony Pérez *  379\n",
            "73  74.0           Matt Williams  378\n",
            "74  75.0               Norm Cash  377\n",
            "\n",
            "[75 rows x 3 columns]},\n",
            "    {   'answer': 'Babe Ruth *',\n",
            "        'context':     Rank       Player (2018 HRs)   HR\n",
            "0    1.0             Barry Bonds  762\n",
            "1    2.0            Hank Aaron *  755\n",
            "2    3.0             Babe Ruth *  714\n",
            "3    4.0          Alex Rodriguez  696\n",
            "4    5.0           Willie Mays *  660\n",
            "..   ...                     ...  ...\n",
            "70  71.0  Edwin Encarnación (32)  380\n",
            "71  72.0        Orlando Cepeda *  379\n",
            "72   nan            Tony Pérez *  379\n",
            "73  74.0           Matt Williams  378\n",
            "74  75.0               Norm Cash  377\n",
            "\n",
            "[75 rows x 3 columns]},\n",
            "    {   'answer': 'Alianza Lima',\n",
            "        'context':                          Team           Manager              Captain  \\\n",
            "0                Alianza Lima         José Soto            Juan Jayo   \n",
            "1                   Cienciano        Raul Arias         Julio Garcia   \n",
            "2                    Cobresol   Octavio Vidales    Gregorio Bernales   \n",
            "3                    Inti Gas      Edgar Ospina        Nick Montalva   \n",
            "4                 José Gálvez       Javier Arce           Marco Ruiz   \n",
            "5                 Juan Aurich    Franco Navarro       Luis Guadalupe   \n",
            "6             León de Huánuco      Jean Ferrari       Carlos Zegarra   \n",
            "7                      Melgar      Julio Zamora  Antonio Meza Cuadra   \n",
            "8              Real Garcilaso     Freddy García      Ramón Rodríguez   \n",
            "9                  Sport Boys      Jorge Espejo         Jorge Huamán   \n",
            "10             Sport Huancayo   Wilmar Valencia        Sergio Ibarra   \n",
            "11           Sporting Cristal  Roberto Mosquera        Erick Delgado   \n",
            "12             Unión Comercio       Mario Viera          Héctor Sosa   \n",
            "13  Universidad César Vallejo     Víctor Rivera        Carlos Galván   \n",
            "14     Universidad San Martín       Angel Cappa          Leao Butrón   \n",
            "15              Universitario   Nolberto Solano       John Galliquio   \n",
            "\n",
            "   Kit manufacturer                 Shirt sponsor  \n",
            "0              Nike                           nan  \n",
            "1             Aries                      Movistar  \n",
            "2           Loma 's     Universidad Alas Peruanas  \n",
            "3             Walon                      Inti Gas  \n",
            "4              Real          SIDERPERU /Megaplaza  \n",
            "5             Walon                  Grupo Oviedo  \n",
            "6             Walon                       Roky 's  \n",
            "7          Marathon                           nan  \n",
            "8             Walon                         I-RUN  \n",
            "9         Triathlon  Gobierno Regional del Callao  \n",
            "10         Manchete    Caja Municipal de Huancayo  \n",
            "11            Umbro  Cerveza Cristal / Volkswagen  \n",
            "12             Real                   New Holland  \n",
            "13            Walon     Universidad César Vallejo  \n",
            "14            Umbro                     Herbalife  \n",
            "15            Umbro                 Radio Exitosa  },\n",
            "    {   'answer': 'Alexander Graham Bell Alexander Graham Bell',\n",
            "        'context': 'is grandchildren. \"U.S. patent images in TIFF format\" '\n",
            "                   'Alexander Graham Bell Alexander Graham Bell (March 3, 1847 '\n",
            "                   '– August 2, 1922) was a Scottish-born'},\n",
            "    {   'answer': 'Gerry Bertier Gerry Bertier (, with a hard \"G\"; August 20, '\n",
            "                  '1953 – March 20, 1981) was a prominent Alexandria, Virginia '\n",
            "                  'high school American football player. He is best known for '\n",
            "                  'his participation on the 1971 Virginia State Champion '\n",
            "                  'football T. C. Williams High School team and their '\n",
            "                  'portrayal in the Disney film \"Remember the Titans\", and '\n",
            "                  'being the nephew of Howard Livingston.',\n",
            "        'context': 'Gerry Bertier Gerry Bertier (, with a hard \"G\"; August 20, '\n",
            "                   '1953 – March 20, 1981) was a prominent Alexandria, '\n",
            "                   'Virginia high school American football player. He is best '\n",
            "                   'known for his participation on the 1971 Virginia State '\n",
            "                   'Champion football T. C. Williams High School team and '\n",
            "                   'their portrayal in the Disney film \"Remember the Titans\", '\n",
            "                   'and being the nephew of Howard Livingston. '},\n",
            "    {   'answer': 'first vice president',\n",
            "        'context': 'active in the Screen Actors Guild. In 2002 he was elected '\n",
            "                   'first vice president of the Guild in Los Angeles and '\n",
            "                   'served in the post for three years. Mik'}]\n"
          ]
        }
      ],
      "source": [
        "# We can see both text passages and tables as contexts of the predicted answers.\n",
        "print_answers(predictions, details=\"minimum\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "QYOHDSmLpzEg",
        "outputId": "a460ecb4-78b8-4859-e601-763276f1d7f0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Inferencing Samples:   0%|          | 0/1 [00:00<?, ? Batches/s]/usr/local/lib/python3.7/dist-packages/haystack/modeling/model/prediction_head.py:478: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
            "  start_indices = flat_sorted_indices // max_seq_len\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  7.81 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 14.40 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 16.15 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 14.52 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 15.69 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 16.31 Batches/s]\n"
          ]
        }
      ],
      "source": [
        "# Example query whose answer resides in a table\n",
        "predictions = text_table_qa_pipeline.run(query=\"Which country does the film Macaroni come from?\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4kw53uWep3zj",
        "outputId": "92ce11f6-1c62-45de-cd0b-fc654c7e16cc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Query: Which country does the film Macaroni come from?\n",
            "Answers:\n",
            "[   {   'answer': 'Italian',\n",
            "        'context':    Submitting country Film title used in nomination        Language ( s )  \\\n",
            "0           Argentina            The Official Story               Spanish   \n",
            "1             Austria                       Malambo                German   \n",
            "2             Belgium                          Dust                French   \n",
            "3              Canada          Jacques and November                French   \n",
            "4      Czechoslovakia              Scalpel , Please                 Czech   \n",
            "5             Denmark               Twist and Shout                Danish   \n",
            "6              France        Three Men and a Cradle                French   \n",
            "7        West Germany                 Angry Harvest                German   \n",
            "8             Hungary                  Colonel Redl                German   \n",
            "9             Iceland                   Deep Winter             Icelandic   \n",
            "10              India                        Saagar                 Hindi   \n",
            "11             Israel              When Night Falls                Hebrew   \n",
            "12              Italy                      Macaroni               Italian   \n",
            "13              Japan                   Gray Sunset              Japanese   \n",
            "14        South Korea                       Eoudong                Korean   \n",
            "15             Mexico              Frida Still Life               Spanish   \n",
            "16        Netherlands                     The Dream  Dutch , West Frisian   \n",
            "17             Norway       Wives - Ten Years After             Norwegian   \n",
            "18               Peru         The City and the Dogs               Spanish   \n",
            "19        Philippines            This Is My Country               Tagalog   \n",
            "\n",
            "                 Original title                     Director ( s )  \\\n",
            "0           La Historia oficial                        Luis Puenzo   \n",
            "1                       Malambo                          Milan Dor   \n",
            "2                          Dust                      Marion Hänsel   \n",
            "3           Jacques et novembre  Jean Beaudry and François Bouvier   \n",
            "4              Skalpel , prosím                       Jirí Svoboda   \n",
            "5        Tro , håb og kærlighed                       Bille August   \n",
            "6    Trois hommes et un couffin                     Coline Serreau   \n",
            "7                 Bittere Ernte                  Agnieszka Holland   \n",
            "8                   Oberst Redl                       István Szabó   \n",
            "9                     Skammdegi                  Þráinn Bertelsson   \n",
            "10                         सागर                       Ramesh Sippy   \n",
            "11                 עד סוף הלילה                        Eitan Green   \n",
            "12                   Maccheroni                       Ettore Scola   \n",
            "13                       花いちもんめ                         Shunya Ito   \n",
            "14                          어우동                        Lee Jang-ho   \n",
            "15      Frida , naturaleza viva                         Paul Leduc   \n",
            "16                     De Dream                    Pieter Verhoeff   \n",
            "17       Hustruer - ti år etter                        Anja Breien   \n",
            "18       La ciudad y los perros            Francisco José Lombardi   \n",
            "19  Bayan ko : Kapit sa patalim                        Lino Brocka   \n",
            "\n",
            "               Result  \n",
            "0   Won Academy Award  \n",
            "1       Not Nominated  \n",
            "2       Not Nominated  \n",
            "3       Not Nominated  \n",
            "4       Not Nominated  \n",
            "5       Not Nominated  \n",
            "6           Nominated  \n",
            "7           Nominated  \n",
            "8           Nominated  \n",
            "9       Not Nominated  \n",
            "10      Not Nominated  \n",
            "11      Not Nominated  \n",
            "12      Not Nominated  \n",
            "13      Not Nominated  \n",
            "14      Not Nominated  \n",
            "15      Not Nominated  \n",
            "16      Not Nominated  \n",
            "17      Not Nominated  \n",
            "18      Not Nominated  \n",
            "19      Not Nominated  },\n",
            "    {   'answer': 'Italian',\n",
            "        'context':    Submitting country Film title used in nomination        Language ( s )  \\\n",
            "0           Argentina            The Official Story               Spanish   \n",
            "1             Austria                       Malambo                German   \n",
            "2             Belgium                          Dust                French   \n",
            "3              Canada          Jacques and November                French   \n",
            "4      Czechoslovakia              Scalpel , Please                 Czech   \n",
            "5             Denmark               Twist and Shout                Danish   \n",
            "6              France        Three Men and a Cradle                French   \n",
            "7        West Germany                 Angry Harvest                German   \n",
            "8             Hungary                  Colonel Redl                German   \n",
            "9             Iceland                   Deep Winter             Icelandic   \n",
            "10              India                        Saagar                 Hindi   \n",
            "11             Israel              When Night Falls                Hebrew   \n",
            "12              Italy                      Macaroni               Italian   \n",
            "13              Japan                   Gray Sunset              Japanese   \n",
            "14        South Korea                       Eoudong                Korean   \n",
            "15             Mexico              Frida Still Life               Spanish   \n",
            "16        Netherlands                     The Dream  Dutch , West Frisian   \n",
            "17             Norway       Wives - Ten Years After             Norwegian   \n",
            "18               Peru         The City and the Dogs               Spanish   \n",
            "19        Philippines            This Is My Country               Tagalog   \n",
            "\n",
            "                 Original title                     Director ( s )  \\\n",
            "0           La Historia oficial                        Luis Puenzo   \n",
            "1                       Malambo                          Milan Dor   \n",
            "2                          Dust                      Marion Hänsel   \n",
            "3           Jacques et novembre  Jean Beaudry and François Bouvier   \n",
            "4              Skalpel , prosím                       Jirí Svoboda   \n",
            "5        Tro , håb og kærlighed                       Bille August   \n",
            "6    Trois hommes et un couffin                     Coline Serreau   \n",
            "7                 Bittere Ernte                  Agnieszka Holland   \n",
            "8                   Oberst Redl                       István Szabó   \n",
            "9                     Skammdegi                  Þráinn Bertelsson   \n",
            "10                         सागर                       Ramesh Sippy   \n",
            "11                 עד סוף הלילה                        Eitan Green   \n",
            "12                   Maccheroni                       Ettore Scola   \n",
            "13                       花いちもんめ                         Shunya Ito   \n",
            "14                          어우동                        Lee Jang-ho   \n",
            "15      Frida , naturaleza viva                         Paul Leduc   \n",
            "16                     De Dream                    Pieter Verhoeff   \n",
            "17       Hustruer - ti år etter                        Anja Breien   \n",
            "18       La ciudad y los perros            Francisco José Lombardi   \n",
            "19  Bayan ko : Kapit sa patalim                        Lino Brocka   \n",
            "\n",
            "               Result  \n",
            "0   Won Academy Award  \n",
            "1       Not Nominated  \n",
            "2       Not Nominated  \n",
            "3       Not Nominated  \n",
            "4       Not Nominated  \n",
            "5       Not Nominated  \n",
            "6           Nominated  \n",
            "7           Nominated  \n",
            "8           Nominated  \n",
            "9       Not Nominated  \n",
            "10      Not Nominated  \n",
            "11      Not Nominated  \n",
            "12      Not Nominated  \n",
            "13      Not Nominated  \n",
            "14      Not Nominated  \n",
            "15      Not Nominated  \n",
            "16      Not Nominated  \n",
            "17      Not Nominated  \n",
            "18      Not Nominated  \n",
            "19      Not Nominated  },\n",
            "    {   'answer': 'Icelandic',\n",
            "        'context':    Submitting country Film title used in nomination        Language ( s )  \\\n",
            "0           Argentina            The Official Story               Spanish   \n",
            "1             Austria                       Malambo                German   \n",
            "2             Belgium                          Dust                French   \n",
            "3              Canada          Jacques and November                French   \n",
            "4      Czechoslovakia              Scalpel , Please                 Czech   \n",
            "5             Denmark               Twist and Shout                Danish   \n",
            "6              France        Three Men and a Cradle                French   \n",
            "7        West Germany                 Angry Harvest                German   \n",
            "8             Hungary                  Colonel Redl                German   \n",
            "9             Iceland                   Deep Winter             Icelandic   \n",
            "10              India                        Saagar                 Hindi   \n",
            "11             Israel              When Night Falls                Hebrew   \n",
            "12              Italy                      Macaroni               Italian   \n",
            "13              Japan                   Gray Sunset              Japanese   \n",
            "14        South Korea                       Eoudong                Korean   \n",
            "15             Mexico              Frida Still Life               Spanish   \n",
            "16        Netherlands                     The Dream  Dutch , West Frisian   \n",
            "17             Norway       Wives - Ten Years After             Norwegian   \n",
            "18               Peru         The City and the Dogs               Spanish   \n",
            "19        Philippines            This Is My Country               Tagalog   \n",
            "\n",
            "                 Original title                     Director ( s )  \\\n",
            "0           La Historia oficial                        Luis Puenzo   \n",
            "1                       Malambo                          Milan Dor   \n",
            "2                          Dust                      Marion Hänsel   \n",
            "3           Jacques et novembre  Jean Beaudry and François Bouvier   \n",
            "4              Skalpel , prosím                       Jirí Svoboda   \n",
            "5        Tro , håb og kærlighed                       Bille August   \n",
            "6    Trois hommes et un couffin                     Coline Serreau   \n",
            "7                 Bittere Ernte                  Agnieszka Holland   \n",
            "8                   Oberst Redl                       István Szabó   \n",
            "9                     Skammdegi                  Þráinn Bertelsson   \n",
            "10                         सागर                       Ramesh Sippy   \n",
            "11                 עד סוף הלילה                        Eitan Green   \n",
            "12                   Maccheroni                       Ettore Scola   \n",
            "13                       花いちもんめ                         Shunya Ito   \n",
            "14                          어우동                        Lee Jang-ho   \n",
            "15      Frida , naturaleza viva                         Paul Leduc   \n",
            "16                     De Dream                    Pieter Verhoeff   \n",
            "17       Hustruer - ti år etter                        Anja Breien   \n",
            "18       La ciudad y los perros            Francisco José Lombardi   \n",
            "19  Bayan ko : Kapit sa patalim                        Lino Brocka   \n",
            "\n",
            "               Result  \n",
            "0   Won Academy Award  \n",
            "1       Not Nominated  \n",
            "2       Not Nominated  \n",
            "3       Not Nominated  \n",
            "4       Not Nominated  \n",
            "5       Not Nominated  \n",
            "6           Nominated  \n",
            "7           Nominated  \n",
            "8           Nominated  \n",
            "9       Not Nominated  \n",
            "10      Not Nominated  \n",
            "11      Not Nominated  \n",
            "12      Not Nominated  \n",
            "13      Not Nominated  \n",
            "14      Not Nominated  \n",
            "15      Not Nominated  \n",
            "16      Not Nominated  \n",
            "17      Not Nominated  \n",
            "18      Not Nominated  \n",
            "19      Not Nominated  },\n",
            "    {   'answer': 'Icelandic',\n",
            "        'context':    Submitting country Film title used in nomination        Language ( s )  \\\n",
            "0           Argentina            The Official Story               Spanish   \n",
            "1             Austria                       Malambo                German   \n",
            "2             Belgium                          Dust                French   \n",
            "3              Canada          Jacques and November                French   \n",
            "4      Czechoslovakia              Scalpel , Please                 Czech   \n",
            "5             Denmark               Twist and Shout                Danish   \n",
            "6              France        Three Men and a Cradle                French   \n",
            "7        West Germany                 Angry Harvest                German   \n",
            "8             Hungary                  Colonel Redl                German   \n",
            "9             Iceland                   Deep Winter             Icelandic   \n",
            "10              India                        Saagar                 Hindi   \n",
            "11             Israel              When Night Falls                Hebrew   \n",
            "12              Italy                      Macaroni               Italian   \n",
            "13              Japan                   Gray Sunset              Japanese   \n",
            "14        South Korea                       Eoudong                Korean   \n",
            "15             Mexico              Frida Still Life               Spanish   \n",
            "16        Netherlands                     The Dream  Dutch , West Frisian   \n",
            "17             Norway       Wives - Ten Years After             Norwegian   \n",
            "18               Peru         The City and the Dogs               Spanish   \n",
            "19        Philippines            This Is My Country               Tagalog   \n",
            "\n",
            "                 Original title                     Director ( s )  \\\n",
            "0           La Historia oficial                        Luis Puenzo   \n",
            "1                       Malambo                          Milan Dor   \n",
            "2                          Dust                      Marion Hänsel   \n",
            "3           Jacques et novembre  Jean Beaudry and François Bouvier   \n",
            "4              Skalpel , prosím                       Jirí Svoboda   \n",
            "5        Tro , håb og kærlighed                       Bille August   \n",
            "6    Trois hommes et un couffin                     Coline Serreau   \n",
            "7                 Bittere Ernte                  Agnieszka Holland   \n",
            "8                   Oberst Redl                       István Szabó   \n",
            "9                     Skammdegi                  Þráinn Bertelsson   \n",
            "10                         सागर                       Ramesh Sippy   \n",
            "11                 עד סוף הלילה                        Eitan Green   \n",
            "12                   Maccheroni                       Ettore Scola   \n",
            "13                       花いちもんめ                         Shunya Ito   \n",
            "14                          어우동                        Lee Jang-ho   \n",
            "15      Frida , naturaleza viva                         Paul Leduc   \n",
            "16                     De Dream                    Pieter Verhoeff   \n",
            "17       Hustruer - ti år etter                        Anja Breien   \n",
            "18       La ciudad y los perros            Francisco José Lombardi   \n",
            "19  Bayan ko : Kapit sa patalim                        Lino Brocka   \n",
            "\n",
            "               Result  \n",
            "0   Won Academy Award  \n",
            "1       Not Nominated  \n",
            "2       Not Nominated  \n",
            "3       Not Nominated  \n",
            "4       Not Nominated  \n",
            "5       Not Nominated  \n",
            "6           Nominated  \n",
            "7           Nominated  \n",
            "8           Nominated  \n",
            "9       Not Nominated  \n",
            "10      Not Nominated  \n",
            "11      Not Nominated  \n",
            "12      Not Nominated  \n",
            "13      Not Nominated  \n",
            "14      Not Nominated  \n",
            "15      Not Nominated  \n",
            "16      Not Nominated  \n",
            "17      Not Nominated  \n",
            "18      Not Nominated  \n",
            "19      Not Nominated  },\n",
            "    {   'answer': 'Japanese',\n",
            "        'context':    Submitting country Film title used in nomination        Language ( s )  \\\n",
            "0           Argentina            The Official Story               Spanish   \n",
            "1             Austria                       Malambo                German   \n",
            "2             Belgium                          Dust                French   \n",
            "3              Canada          Jacques and November                French   \n",
            "4      Czechoslovakia              Scalpel , Please                 Czech   \n",
            "5             Denmark               Twist and Shout                Danish   \n",
            "6              France        Three Men and a Cradle                French   \n",
            "7        West Germany                 Angry Harvest                German   \n",
            "8             Hungary                  Colonel Redl                German   \n",
            "9             Iceland                   Deep Winter             Icelandic   \n",
            "10              India                        Saagar                 Hindi   \n",
            "11             Israel              When Night Falls                Hebrew   \n",
            "12              Italy                      Macaroni               Italian   \n",
            "13              Japan                   Gray Sunset              Japanese   \n",
            "14        South Korea                       Eoudong                Korean   \n",
            "15             Mexico              Frida Still Life               Spanish   \n",
            "16        Netherlands                     The Dream  Dutch , West Frisian   \n",
            "17             Norway       Wives - Ten Years After             Norwegian   \n",
            "18               Peru         The City and the Dogs               Spanish   \n",
            "19        Philippines            This Is My Country               Tagalog   \n",
            "\n",
            "                 Original title                     Director ( s )  \\\n",
            "0           La Historia oficial                        Luis Puenzo   \n",
            "1                       Malambo                          Milan Dor   \n",
            "2                          Dust                      Marion Hänsel   \n",
            "3           Jacques et novembre  Jean Beaudry and François Bouvier   \n",
            "4              Skalpel , prosím                       Jirí Svoboda   \n",
            "5        Tro , håb og kærlighed                       Bille August   \n",
            "6    Trois hommes et un couffin                     Coline Serreau   \n",
            "7                 Bittere Ernte                  Agnieszka Holland   \n",
            "8                   Oberst Redl                       István Szabó   \n",
            "9                     Skammdegi                  Þráinn Bertelsson   \n",
            "10                         सागर                       Ramesh Sippy   \n",
            "11                 עד סוף הלילה                        Eitan Green   \n",
            "12                   Maccheroni                       Ettore Scola   \n",
            "13                       花いちもんめ                         Shunya Ito   \n",
            "14                          어우동                        Lee Jang-ho   \n",
            "15      Frida , naturaleza viva                         Paul Leduc   \n",
            "16                     De Dream                    Pieter Verhoeff   \n",
            "17       Hustruer - ti år etter                        Anja Breien   \n",
            "18       La ciudad y los perros            Francisco José Lombardi   \n",
            "19  Bayan ko : Kapit sa patalim                        Lino Brocka   \n",
            "\n",
            "               Result  \n",
            "0   Won Academy Award  \n",
            "1       Not Nominated  \n",
            "2       Not Nominated  \n",
            "3       Not Nominated  \n",
            "4       Not Nominated  \n",
            "5       Not Nominated  \n",
            "6           Nominated  \n",
            "7           Nominated  \n",
            "8           Nominated  \n",
            "9       Not Nominated  \n",
            "10      Not Nominated  \n",
            "11      Not Nominated  \n",
            "12      Not Nominated  \n",
            "13      Not Nominated  \n",
            "14      Not Nominated  \n",
            "15      Not Nominated  \n",
            "16      Not Nominated  \n",
            "17      Not Nominated  \n",
            "18      Not Nominated  \n",
            "19      Not Nominated  },\n",
            "    {   'answer': 'Japanese',\n",
            "        'context':    Submitting country Film title used in nomination        Language ( s )  \\\n",
            "0           Argentina            The Official Story               Spanish   \n",
            "1             Austria                       Malambo                German   \n",
            "2             Belgium                          Dust                French   \n",
            "3              Canada          Jacques and November                French   \n",
            "4      Czechoslovakia              Scalpel , Please                 Czech   \n",
            "5             Denmark               Twist and Shout                Danish   \n",
            "6              France        Three Men and a Cradle                French   \n",
            "7        West Germany                 Angry Harvest                German   \n",
            "8             Hungary                  Colonel Redl                German   \n",
            "9             Iceland                   Deep Winter             Icelandic   \n",
            "10              India                        Saagar                 Hindi   \n",
            "11             Israel              When Night Falls                Hebrew   \n",
            "12              Italy                      Macaroni               Italian   \n",
            "13              Japan                   Gray Sunset              Japanese   \n",
            "14        South Korea                       Eoudong                Korean   \n",
            "15             Mexico              Frida Still Life               Spanish   \n",
            "16        Netherlands                     The Dream  Dutch , West Frisian   \n",
            "17             Norway       Wives - Ten Years After             Norwegian   \n",
            "18               Peru         The City and the Dogs               Spanish   \n",
            "19        Philippines            This Is My Country               Tagalog   \n",
            "\n",
            "                 Original title                     Director ( s )  \\\n",
            "0           La Historia oficial                        Luis Puenzo   \n",
            "1                       Malambo                          Milan Dor   \n",
            "2                          Dust                      Marion Hänsel   \n",
            "3           Jacques et novembre  Jean Beaudry and François Bouvier   \n",
            "4              Skalpel , prosím                       Jirí Svoboda   \n",
            "5        Tro , håb og kærlighed                       Bille August   \n",
            "6    Trois hommes et un couffin                     Coline Serreau   \n",
            "7                 Bittere Ernte                  Agnieszka Holland   \n",
            "8                   Oberst Redl                       István Szabó   \n",
            "9                     Skammdegi                  Þráinn Bertelsson   \n",
            "10                         सागर                       Ramesh Sippy   \n",
            "11                 עד סוף הלילה                        Eitan Green   \n",
            "12                   Maccheroni                       Ettore Scola   \n",
            "13                       花いちもんめ                         Shunya Ito   \n",
            "14                          어우동                        Lee Jang-ho   \n",
            "15      Frida , naturaleza viva                         Paul Leduc   \n",
            "16                     De Dream                    Pieter Verhoeff   \n",
            "17       Hustruer - ti år etter                        Anja Breien   \n",
            "18       La ciudad y los perros            Francisco José Lombardi   \n",
            "19  Bayan ko : Kapit sa patalim                        Lino Brocka   \n",
            "\n",
            "               Result  \n",
            "0   Won Academy Award  \n",
            "1       Not Nominated  \n",
            "2       Not Nominated  \n",
            "3       Not Nominated  \n",
            "4       Not Nominated  \n",
            "5       Not Nominated  \n",
            "6           Nominated  \n",
            "7           Nominated  \n",
            "8           Nominated  \n",
            "9       Not Nominated  \n",
            "10      Not Nominated  \n",
            "11      Not Nominated  \n",
            "12      Not Nominated  \n",
            "13      Not Nominated  \n",
            "14      Not Nominated  \n",
            "15      Not Nominated  \n",
            "16      Not Nominated  \n",
            "17      Not Nominated  \n",
            "18      Not Nominated  \n",
            "19      Not Nominated  },\n",
            "    {   'answer': 'Strength',\n",
            "        'context':                                        \\\n",
            "0  Vietnam War (Chiến tranh Việt Nam)   \n",
            "\n",
            "                                                \\\n",
            "0  Part of the Indochina Wars and the Cold War   \n",
            "\n",
            "                                                                                    \\\n",
            "0  Clockwise, from top left: U.S. combat operations in Ia Drang, ARVN Rangers d...   \n",
            "\n",
            "                                                                                    \\\n",
            "0  Date 1 November 1955[A 1] – 30 April 1975 (19 years, 5 months, 4 weeks and 1...   \n",
            "\n",
            "                                                                           Date  \\\n",
            "0  1 November 1955[A 1] – 30 April 1975 (19 years, 5 months, 4 weeks and 1 day)   \n",
            "\n",
            "                                                                          Location  \\\n",
            "0  South Vietnam, North Vietnam, Cambodia, Laos, South China Sea, Gulf of Thailand   \n",
            "\n",
            "                                                                            Result  \\\n",
            "0  North Vietnamese victory Withdrawal of American-led forces from Indochina Co...   \n",
            "\n",
            "                                                               Territorial changes  \\\n",
            "0  Reunification of North and South Vietnam into the Socialist Republic of Viet...   \n",
            "\n",
            "                 \\\n",
            "0  Belligerents   \n",
            "\n",
            "  South Vietnam  United States  South Korea  Thailand  Australia  Philippines  New Zealand  Khmer Republic  Kingdom of Laos Military support:  Taiwan[1][2] Other support[show]  Malaysia[3][4]  Spain[2]  Canada [2]  Iran[2]  West Germany[2]  Brazil[5]  Japan[2]  \\\n",
            "0  North Vietnam  Viet Cong  Khmer Rouge  Pathet Lao  China  North Korea Milita...                                                                                                                                                                                     \n",
            "\n",
            "                           \\\n",
            "0  Commanders and leaders   \n",
            "\n",
            "  Ngô Đình Diệm †  Nguyễn Văn Thiệu  Nguyễn Cao Kỳ  Cao Văn Viên  Ngô Quang Trưởng  John F. Kennedy  Lyndon B. Johnson  Richard Nixon  Gerald Ford  Robert McNamara  William Westmoreland  Creighton Abrams  Frederick C. Weyand  Park Chung-hee  Thanom Kittikachorn  Robert Menzies  Harold Holt  John McEwen  John Gorton  William McMahon  Ferdinand Marcos  Keith Holyoake  Jack Marshall  Norman Kirk  Chiang Kai-Shek …and others  \\\n",
            "0  Ho Chi Minh  Lê Duẩn  Võ Nguyên Giáp  Văn Tiến Dũng  Lê Trọng Tấn  Phạm Văn ...                                                                                                                                                                                                                                                                                                                                                         \n",
            "\n",
            "             \\\n",
            "0  Strength   \n",
            "\n",
            "  ≈1,420,000 (1968)  South Vietnam: 850,000 (1968) 1,500,000 (1974–75)[21]  United States: 543,000 (April 1969)[22][23]  South Korea: 50,003  Thailand: 11,570[24]  Australia: 7,672  Philippines: 2,061  New Zealand: 552[25]  \\\n",
            "0  ≈1,060,000 (1967)  North Vietnam: 690,000 (January 1967)[26]  Viet Cong: 200...                                                                                                                                               \n",
            "\n",
            "                          \\\n",
            "0  Casualties and losses   \n",
            "\n",
            "  South Vietnam 195,000–430,000 civilian dead[32][33][34] 220,357[35]–313,000 military dead[36] 1,170,000 wounded[37]  United States 58,220 dead;[38] 303,644 wounded (including 150,341 not requiring hospital care)[A 2]  South Korea 5,099 dead; 10,962 wounded; 4 missing  Australia 521 dead; 3,129 wounded [43]  Thailand 351 dead; 1,358 wounded[44]  New Zealand 37 dead; 187 wounded[45]  Taiwan 25 dead;[46]  Philippines 9 dead;[47] 64 wounded[48] Total military dead: 284,668–377,311 Total wounded: ≈1,340,000+[37]  \\\n",
            "0  North Vietnam & Viet Cong 65,000 civilian dead[33] 849,018 military dead[49]...                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
            "\n",
            "                                                                                    \n",
            "0  Vietnamese civilian dead: 627,000–2,000,000[33][53][54] Vietnamese total dea...  },\n",
            "    {   'answer': 'Ho Chi Minh  Lê Duẩn  Võ Nguyên Giáp  Văn Tiến Dũng  Lê '\n",
            "                  'Trọng Tấn  Phạm Văn Đồng  Hoàng Văn Thái  Trần Văn Trà  '\n",
            "                  'Nguyễn Văn Linh  Nguyễn Hữu Thọ …and others',\n",
            "        'context':                                        \\\n",
            "0  Vietnam War (Chiến tranh Việt Nam)   \n",
            "\n",
            "                                                \\\n",
            "0  Part of the Indochina Wars and the Cold War   \n",
            "\n",
            "                                                                                    \\\n",
            "0  Clockwise, from top left: U.S. combat operations in Ia Drang, ARVN Rangers d...   \n",
            "\n",
            "                                                                                    \\\n",
            "0  Date 1 November 1955[A 1] – 30 April 1975 (19 years, 5 months, 4 weeks and 1...   \n",
            "\n",
            "                                                                           Date  \\\n",
            "0  1 November 1955[A 1] – 30 April 1975 (19 years, 5 months, 4 weeks and 1 day)   \n",
            "\n",
            "                                                                          Location  \\\n",
            "0  South Vietnam, North Vietnam, Cambodia, Laos, South China Sea, Gulf of Thailand   \n",
            "\n",
            "                                                                            Result  \\\n",
            "0  North Vietnamese victory Withdrawal of American-led forces from Indochina Co...   \n",
            "\n",
            "                                                               Territorial changes  \\\n",
            "0  Reunification of North and South Vietnam into the Socialist Republic of Viet...   \n",
            "\n",
            "                 \\\n",
            "0  Belligerents   \n",
            "\n",
            "  South Vietnam  United States  South Korea  Thailand  Australia  Philippines  New Zealand  Khmer Republic  Kingdom of Laos Military support:  Taiwan[1][2] Other support[show]  Malaysia[3][4]  Spain[2]  Canada [2]  Iran[2]  West Germany[2]  Brazil[5]  Japan[2]  \\\n",
            "0  North Vietnam  Viet Cong  Khmer Rouge  Pathet Lao  China  North Korea Milita...                                                                                                                                                                                     \n",
            "\n",
            "                           \\\n",
            "0  Commanders and leaders   \n",
            "\n",
            "  Ngô Đình Diệm †  Nguyễn Văn Thiệu  Nguyễn Cao Kỳ  Cao Văn Viên  Ngô Quang Trưởng  John F. Kennedy  Lyndon B. Johnson  Richard Nixon  Gerald Ford  Robert McNamara  William Westmoreland  Creighton Abrams  Frederick C. Weyand  Park Chung-hee  Thanom Kittikachorn  Robert Menzies  Harold Holt  John McEwen  John Gorton  William McMahon  Ferdinand Marcos  Keith Holyoake  Jack Marshall  Norman Kirk  Chiang Kai-Shek …and others  \\\n",
            "0  Ho Chi Minh  Lê Duẩn  Võ Nguyên Giáp  Văn Tiến Dũng  Lê Trọng Tấn  Phạm Văn ...                                                                                                                                                                                                                                                                                                                                                         \n",
            "\n",
            "             \\\n",
            "0  Strength   \n",
            "\n",
            "  ≈1,420,000 (1968)  South Vietnam: 850,000 (1968) 1,500,000 (1974–75)[21]  United States: 543,000 (April 1969)[22][23]  South Korea: 50,003  Thailand: 11,570[24]  Australia: 7,672  Philippines: 2,061  New Zealand: 552[25]  \\\n",
            "0  ≈1,060,000 (1967)  North Vietnam: 690,000 (January 1967)[26]  Viet Cong: 200...                                                                                                                                               \n",
            "\n",
            "                          \\\n",
            "0  Casualties and losses   \n",
            "\n",
            "  South Vietnam 195,000–430,000 civilian dead[32][33][34] 220,357[35]–313,000 military dead[36] 1,170,000 wounded[37]  United States 58,220 dead;[38] 303,644 wounded (including 150,341 not requiring hospital care)[A 2]  South Korea 5,099 dead; 10,962 wounded; 4 missing  Australia 521 dead; 3,129 wounded [43]  Thailand 351 dead; 1,358 wounded[44]  New Zealand 37 dead; 187 wounded[45]  Taiwan 25 dead;[46]  Philippines 9 dead;[47] 64 wounded[48] Total military dead: 284,668–377,311 Total wounded: ≈1,340,000+[37]  \\\n",
            "0  North Vietnam & Viet Cong 65,000 civilian dead[33] 849,018 military dead[49]...                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
            "\n",
            "                                                                                    \n",
            "0  Vietnamese civilian dead: 627,000–2,000,000[33][53][54] Vietnamese total dea...  },\n",
            "    {   'answer': 'North Vietnam  Viet Cong  Khmer Rouge  Pathet Lao \\xa0'\n",
            "                  'China \\xa0North Korea Military support: \\xa0Soviet '\n",
            "                  'Union \\xa0Cuba[6][7] Other support[show]  '\n",
            "                  'Czechoslovakia[8][9]  Bulgaria[10] \\xa0East '\n",
            "                  'Germany[11][12]  Romania[13] \\xa0Poland[14]  '\n",
            "                  'Hungary[14] \\xa0Sweden[15][16]',\n",
            "        'context':                                        \\\n",
            "0  Vietnam War (Chiến tranh Việt Nam)   \n",
            "\n",
            "                                                \\\n",
            "0  Part of the Indochina Wars and the Cold War   \n",
            "\n",
            "                                                                                    \\\n",
            "0  Clockwise, from top left: U.S. combat operations in Ia Drang, ARVN Rangers d...   \n",
            "\n",
            "                                                                                    \\\n",
            "0  Date 1 November 1955[A 1] – 30 April 1975 (19 years, 5 months, 4 weeks and 1...   \n",
            "\n",
            "                                                                           Date  \\\n",
            "0  1 November 1955[A 1] – 30 April 1975 (19 years, 5 months, 4 weeks and 1 day)   \n",
            "\n",
            "                                                                          Location  \\\n",
            "0  South Vietnam, North Vietnam, Cambodia, Laos, South China Sea, Gulf of Thailand   \n",
            "\n",
            "                                                                            Result  \\\n",
            "0  North Vietnamese victory Withdrawal of American-led forces from Indochina Co...   \n",
            "\n",
            "                                                               Territorial changes  \\\n",
            "0  Reunification of North and South Vietnam into the Socialist Republic of Viet...   \n",
            "\n",
            "                 \\\n",
            "0  Belligerents   \n",
            "\n",
            "  South Vietnam  United States  South Korea  Thailand  Australia  Philippines  New Zealand  Khmer Republic  Kingdom of Laos Military support:  Taiwan[1][2] Other support[show]  Malaysia[3][4]  Spain[2]  Canada [2]  Iran[2]  West Germany[2]  Brazil[5]  Japan[2]  \\\n",
            "0  North Vietnam  Viet Cong  Khmer Rouge  Pathet Lao  China  North Korea Milita...                                                                                                                                                                                     \n",
            "\n",
            "                           \\\n",
            "0  Commanders and leaders   \n",
            "\n",
            "  Ngô Đình Diệm †  Nguyễn Văn Thiệu  Nguyễn Cao Kỳ  Cao Văn Viên  Ngô Quang Trưởng  John F. Kennedy  Lyndon B. Johnson  Richard Nixon  Gerald Ford  Robert McNamara  William Westmoreland  Creighton Abrams  Frederick C. Weyand  Park Chung-hee  Thanom Kittikachorn  Robert Menzies  Harold Holt  John McEwen  John Gorton  William McMahon  Ferdinand Marcos  Keith Holyoake  Jack Marshall  Norman Kirk  Chiang Kai-Shek …and others  \\\n",
            "0  Ho Chi Minh  Lê Duẩn  Võ Nguyên Giáp  Văn Tiến Dũng  Lê Trọng Tấn  Phạm Văn ...                                                                                                                                                                                                                                                                                                                                                         \n",
            "\n",
            "             \\\n",
            "0  Strength   \n",
            "\n",
            "  ≈1,420,000 (1968)  South Vietnam: 850,000 (1968) 1,500,000 (1974–75)[21]  United States: 543,000 (April 1969)[22][23]  South Korea: 50,003  Thailand: 11,570[24]  Australia: 7,672  Philippines: 2,061  New Zealand: 552[25]  \\\n",
            "0  ≈1,060,000 (1967)  North Vietnam: 690,000 (January 1967)[26]  Viet Cong: 200...                                                                                                                                               \n",
            "\n",
            "                          \\\n",
            "0  Casualties and losses   \n",
            "\n",
            "  South Vietnam 195,000–430,000 civilian dead[32][33][34] 220,357[35]–313,000 military dead[36] 1,170,000 wounded[37]  United States 58,220 dead;[38] 303,644 wounded (including 150,341 not requiring hospital care)[A 2]  South Korea 5,099 dead; 10,962 wounded; 4 missing  Australia 521 dead; 3,129 wounded [43]  Thailand 351 dead; 1,358 wounded[44]  New Zealand 37 dead; 187 wounded[45]  Taiwan 25 dead;[46]  Philippines 9 dead;[47] 64 wounded[48] Total military dead: 284,668–377,311 Total wounded: ≈1,340,000+[37]  \\\n",
            "0  North Vietnam & Viet Cong 65,000 civilian dead[33] 849,018 military dead[49]...                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
            "\n",
            "                                                                                    \n",
            "0  Vietnamese civilian dead: 627,000–2,000,000[33][53][54] Vietnamese total dea...  },\n",
            "    {   'answer': 'Canada',\n",
            "        'context':    Place                Player           Country         Score To par\n",
            "0      1        Phil Mickelson     United States  70-72-70=212     –4\n",
            "1     T2         Chad Campbell     United States  71-67-75=213     –3\n",
            "2     T2          Fred Couples     United States  71-70-72=213     –3\n",
            "3     T4          Stephen Ames            Canada  74-70-70=214     –2\n",
            "4     T4             Tim Clark      South Africa  70-72-72=214     –2\n",
            "5     T4         Darren Clarke  Northern Ireland  72-70-72=214     –2\n",
            "6     T4         Rocco Mediate     United States  68-73-73=214     –2\n",
            "7     T4           Vijay Singh              Fiji  67-74-73=214     –2\n",
            "8     T4           Tiger Woods     United States  72-71-71=214     –2\n",
            "9    T10         Retief Goosen      South Africa  70-73-72=215     –1\n",
            "10   T10  Miguel Ángel Jiménez             Spain  72-74-69=215     –1},\n",
            "    {   'answer': 'England',\n",
            "        'context': 'd Estate. The exterior of the Cragside country house in '\n",
            "                   'Northumberland, England, along with its coniferous '\n",
            "                   'surroundings, was used to depict the Lockwo'},\n",
            "    {   'answer': 'Miami',\n",
            "        'context': 'uld air on December 18, 2017. On October 30, 2017, VH1 '\n",
            "                   'announced \"\", the Miami-based spin-off of \"Love & Hip '\n",
            "                   'Hop\", would make its series premiere on J'},\n",
            "    {   'answer': 'Southern',\n",
            "        'context': \" Cledus' dog Fred's barking) and music (such as the final \"\n",
            "                   'chase to the Southern Classic) were removed and not '\n",
            "                   'replaced. (Note: earlier DVD releases an'},\n",
            "    {   'answer': 'Scotland',\n",
            "        'context': 'it with them to other regions, notably Scotland and the '\n",
            "                   'Isle of Man, where Middle Irish gave rise to Scottish '\n",
            "                   'Gaelic and Manx respectively. It has the'},\n",
            "    {   'answer': 'American',\n",
            "        'context': 'film) Rhapsody in Blue is a 1945 fictionalized screen '\n",
            "                   'biography of the American composer and musician George '\n",
            "                   'Gershwin (September 26, 1898 – July 11, 1'},\n",
            "    {   'answer': 'United States',\n",
            "        'context': ' in the film\\'s financing and production. \"The Terminator\" '\n",
            "                   'topped the United States box office for two weeks and '\n",
            "                   \"helped launch Cameron's film career an\"}]\n"
          ]
        }
      ],
      "source": [
        "# We can see both text passages and tables as contexts of the predicted answers.\n",
        "print_answers(predictions, details=\"minimum\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DSz7oIKj6X0j"
      },
      "source": [
        "## Evaluation\n",
        "To evaluate our pipeline, we can use haystack's evaluation feature. We just need to convert our labels into `MultiLabel` objects and the `eval` method will do the rest."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "hJ4Q81FE6X0j"
      },
      "outputs": [],
      "source": [
        "from haystack import Label, MultiLabel, Answer\n",
        "\n",
        "\n",
        "def read_labels(filename, tables):\n",
        "    processed_labels = []\n",
        "    with open(filename) as labels:\n",
        "        labels = json.load(labels)\n",
        "        for table in tables:\n",
        "            if table.id not in labels:\n",
        "                continue\n",
        "            label = labels[table.id]\n",
        "            label = Label(\n",
        "                query=label[\"query\"],\n",
        "                document=table,\n",
        "                is_correct_answer=True,\n",
        "                is_correct_document=True,\n",
        "                answer=Answer(answer=label[\"answer\"]),\n",
        "                origin=\"gold-label\",\n",
        "            )\n",
        "            processed_labels.append(MultiLabel(labels=[label]))\n",
        "    return processed_labels\n",
        "\n",
        "\n",
        "table_labels = read_labels(f\"{doc_dir}/labels.json\", tables)\n",
        "passage_labels = read_labels(f\"{doc_dir}/labels.json\", passages)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "Iaz7agyP6X0k",
        "outputId": "2197f1f1-06ec-470b-a504-5e3cc7613418",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Inferencing Samples:   0%|          | 0/1 [00:00<?, ? Batches/s]/usr/local/lib/python3.7/dist-packages/haystack/modeling/model/prediction_head.py:478: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
            "  start_indices = flat_sorted_indices // max_seq_len\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 15.43 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00, 16.14 Batches/s]\n",
            "Inferencing Samples:   0%|          | 0/1 [00:00<?, ? Batches/s]/usr/local/lib/python3.7/dist-packages/haystack/modeling/model/prediction_head.py:478: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
            "  start_indices = flat_sorted_indices // max_seq_len\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  7.73 Batches/s]\n",
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            "  start_indices = flat_sorted_indices // max_seq_len\n",
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            "  start_indices = flat_sorted_indices // max_seq_len\n",
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            "  start_indices = flat_sorted_indices // max_seq_len\n",
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            "  start_indices = flat_sorted_indices // max_seq_len\n",
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            "  start_indices = flat_sorted_indices // max_seq_len\n",
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          ]
        }
      ],
      "source": [
        "eval_results = text_table_qa_pipeline.eval(table_labels + passage_labels, params={\"top_k\": 10})"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "id": "QlVlB5cl6X0k",
        "outputId": "3b511608-9ef9-4546-f698-facca1724c85",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'JoinAnswers': {'f1': 0.7126190476190477, 'exact_match': 0.6}}\n"
          ]
        }
      ],
      "source": [
        "# Calculating and printing the evaluation metrics\n",
        "print(eval_results.calculate_metrics())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VvVpHUlu6X0k"
      },
      "source": [
        "## Adding tables from PDFs\n",
        "It can sometimes be hard to provide your data in form of a pandas DataFrame. For this case, we provide the `ParsrConverter` wrapper that can help you to convert, for example, a PDF file into a document that you can index."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "id": "oHw3B1YV6X0k",
        "outputId": "619d7b8b-f78d-4a31-e93e-76e2a4332783",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/bin/bash: docker: command not found\n"
          ]
        }
      ],
      "source": [
        "!docker run -d -p 3001:3001 axarev/parsr"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "id": "E31uTyHD6X0k",
        "outputId": "c11a1cf1-3c20-4d45-a66d-3758bff6d4a3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-04-18 23:55:56--  https://www.w3.org/WAI/WCAG21/working-examples/pdf-table/table.pdf\n",
            "Resolving www.w3.org (www.w3.org)... 128.30.52.100\n",
            "Connecting to www.w3.org (www.w3.org)|128.30.52.100|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 66887 (65K) [application/pdf]\n",
            "Saving to: ‘table.pdf’\n",
            "\n",
            "table.pdf           100%[===================>]  65.32K  --.-KB/s    in 0.07s   \n",
            "\n",
            "2022-04-18 23:55:57 (885 KB/s) - ‘table.pdf’ saved [66887/66887]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget https://www.w3.org/WAI/WCAG21/working-examples/pdf-table/table.pdf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "dYmLjkSF6X0k",
        "outputId": "1316350e-6f1b-43be-c59a-50e5a7324777",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 832
        }
      },
      "outputs": [
        {
          "output_type": "error",
          "ename": "Exception",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mConnectionRefusedError\u001b[0m                    Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    158\u001b[0m             conn = connection.create_connection(\n\u001b[0;32m--> 159\u001b[0;31m                 (self._dns_host, self.port), self.timeout, **extra_kw)\n\u001b[0m\u001b[1;32m    160\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     79\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0merr\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 80\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     81\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource_address\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m             \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msa\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mConnectionRefusedError\u001b[0m: [Errno 111] Connection refused",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mNewConnectionError\u001b[0m                        Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    599\u001b[0m                                                   \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 600\u001b[0;31m                                                   chunked=chunked)\n\u001b[0m\u001b[1;32m    601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    353\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 354\u001b[0;31m             \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mhttplib_request_kw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    355\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1280\u001b[0m         \u001b[0;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1281\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1282\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36m_send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1326\u001b[0m             \u001b[0mbody\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'body'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1327\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mendheaders\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36mendheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1275\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mCannotSendHeader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1276\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_output\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage_body\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1277\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36m_send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1035\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1036\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1037\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    975\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_open\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 976\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    977\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    180\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m         \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_new_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    182\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_prepare_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    167\u001b[0m             raise NewConnectionError(\n\u001b[0;32m--> 168\u001b[0;31m                 self, \"Failed to establish a new connection: %s\" % e)\n\u001b[0m\u001b[1;32m    169\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNewConnectionError\u001b[0m: <urllib3.connection.HTTPConnection object at 0x7fbdb9383c10>: Failed to establish a new connection: [Errno 111] Connection refused",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mMaxRetryError\u001b[0m                             Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/requests/adapters.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    448\u001b[0m                     \u001b[0mretries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax_retries\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m                     \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    450\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    637\u001b[0m             retries = retries.increment(method, url, error=e, _pool=self,\n\u001b[0;32m--> 638\u001b[0;31m                                         _stacktrace=sys.exc_info()[2])\n\u001b[0m\u001b[1;32m    639\u001b[0m             \u001b[0mretries\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/urllib3/util/retry.py\u001b[0m in \u001b[0;36mincrement\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m    398\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mnew_retry\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_exhausted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 399\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mMaxRetryError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_pool\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merror\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mResponseError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    400\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mMaxRetryError\u001b[0m: HTTPConnectionPool(host='localhost', port=3001): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fbdb9383c10>: Failed to establish a new connection: [Errno 111] Connection refused'))",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mConnectionError\u001b[0m                           Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/file_converter/parsr.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, parsr_url, extractor, table_detection_mode, preceding_context_len, following_context_len, remove_page_headers, remove_page_footers, remove_table_of_contents, valid_languages, id_hash_keys)\u001b[0m\n\u001b[1;32m     70\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m             \u001b[0mping\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparsr_url\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexceptions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mConnectionError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/requests/api.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(url, params, **kwargs)\u001b[0m\n\u001b[1;32m     75\u001b[0m     \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetdefault\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'allow_redirects'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 76\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'get'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     77\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/requests/api.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(method, url, **kwargs)\u001b[0m\n\u001b[1;32m     60\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0msessions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msession\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 61\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msession\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     62\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/requests/sessions.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m    529\u001b[0m         \u001b[0msend_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msettings\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 530\u001b[0;31m         \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0msend_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    531\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/requests/sessions.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m    642\u001b[0m         \u001b[0;31m# Send the request\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 643\u001b[0;31m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0madapter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    644\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/requests/adapters.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    515\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 516\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mConnectionError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    517\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mConnectionError\u001b[0m: HTTPConnectionPool(host='localhost', port=3001): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fbdb9383c10>: Failed to establish a new connection: [Errno 111] Connection refused'))",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-33-163b98f96b33>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mhaystack\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mParsrConverter\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mconverter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mParsrConverter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mdocs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconverter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"table.pdf\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/base.py\u001b[0m in \u001b[0;36mwrapper_exportable_to_yaml\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m     26\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m         \u001b[0;31m# Call the actuall __init__ function with all the arguments\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m         \u001b[0minit_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     29\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m         \u001b[0;31m# Warn for unnamed input params - should be rare\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/haystack/nodes/file_converter/parsr.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, parsr_url, extractor, table_detection_mode, preceding_context_len, following_context_len, remove_page_headers, remove_page_footers, remove_table_of_contents, valid_languages, id_hash_keys)\u001b[0m\n\u001b[1;32m     72\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexceptions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mConnectionError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m             raise Exception(\n\u001b[0;32m---> 74\u001b[0;31m                 \u001b[0;34mf\"Parsr server is not reachable at the URL '{parsr_url}'. To run it locally \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     75\u001b[0m                 \u001b[0;34mf\"with Docker, execute: 'docker run -p 3001:3001 axarev/parsr:v1.2.2'\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     76\u001b[0m             )\n",
            "\u001b[0;31mException\u001b[0m: Parsr server is not reachable at the URL 'http://localhost:3001'. To run it locally with Docker, execute: 'docker run -p 3001:3001 axarev/parsr:v1.2.2'"
          ]
        }
      ],
      "source": [
        "from haystack.nodes import ParsrConverter\n",
        "\n",
        "converter = ParsrConverter()\n",
        "\n",
        "docs = converter.convert(\"table.pdf\")\n",
        "\n",
        "tables = [doc for doc in docs if doc[\"content_type\"] == \"table\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "IUD8Kb576X0k"
      },
      "outputs": [],
      "source": [
        "print(tables)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RyeK3s28_X1C"
      },
      "source": [
        "## About us\n",
        "\n",
        "This [Haystack](https://github.com/deepset-ai/haystack/) notebook was made with love by [deepset](https://deepset.ai/) in Berlin, Germany\n",
        "\n",
        "We bring NLP to the industry via open source!  \n",
        "Our focus: Industry specific language models & large scale QA systems.  \n",
        "  \n",
        "Some of our other work: \n",
        "- [German BERT](https://deepset.ai/german-bert)\n",
        "- [GermanQuAD and GermanDPR](https://deepset.ai/germanquad)\n",
        "- [FARM](https://github.com/deepset-ai/FARM)\n",
        "\n",
        "Get in touch:\n",
        "[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Slack](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)\n",
        "\n",
        "By the way: [we're hiring!](https://www.deepset.ai/jobs)\n"
      ]
    }
  ],
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