notebooks/biomedical.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "biomedical.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7f4kCuMxQpMH"
      },
      "source": [
        "## Install libraries and models"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BY5lmWPCO4F7"
      },
      "source": [
        "# install >= 3.0.1 spacy version\n",
        "!pip install spacy==3.0.1\n",
        "\n",
        "# install scispacy\n",
        "!pip install scispacy\n",
        "\n",
        "# install models\n",
        "!pip install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.4.0/en_ner_craft_md-0.4.0.tar.gz\n",
        "!pip install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.4.0/en_ner_jnlpba_md-0.4.0.tar.gz\n",
        "!pip install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.4.0/en_ner_bc5cdr_md-0.4.0.tar.gz\n",
        "!pip install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.4.0/en_ner_bionlp13cg_md-0.4.0.tar.gz"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HNzMJm6XII5K"
      },
      "source": [
        "## Importing libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "snEZYaiMErgL"
      },
      "source": [
        "# essentials\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "# spacy\n",
        "import scispacy\n",
        "import spacy\n",
        "\n",
        "# display results\n",
        "from spacy import displacy\n",
        "\n",
        "# scispacy models\n",
        "import en_ner_craft_md\n",
        "import en_ner_jnlpba_md\n",
        "import en_ner_bc5cdr_md\n",
        "import en_ner_bionlp13cg_md\n",
        "\n",
        "# utility\n",
        "from collections import OrderedDict\n",
        "from pprint import pprint\n",
        "\n",
        "# surpress warnings\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "# Data Visualization\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ys-g_WhwWvXe"
      },
      "source": [
        "### Helper funcs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X0fs2ydqHrkD"
      },
      "source": [
        "def missing_cols(df):\n",
        "    '''prints out columns with its amount of missing values with its %'''\n",
        "    total = 0\n",
        "    for col in df.columns:\n",
        "        missing_vals = df[col].isnull().sum()\n",
        "        pct = df[col].isna().mean() * 100\n",
        "        total += missing_vals\n",
        "        if missing_vals != 0:\n",
        "          print('{} => {} [{}%]'.format(col, df[col].isnull().sum(), round(pct, 2)))\n",
        "    \n",
        "    if total == 0:\n",
        "        print(\"no missing values\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "07jmRMn1IGj7"
      },
      "source": [
        "## Loading data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t15bRHgiHsPg"
      },
      "source": [
        "  # Note: this path will be different depending on where you store the dataset\n",
        "data_path = 'PATH_TO_DATA'\n",
        "\n",
        "# Load training datasets\n",
        "abstracts_train = pd.read_csv(data_path + 'abstracts_train.csv', sep='\\t')\n",
        "entities_train = pd.read_csv(data_path + 'entities_train.csv', sep='\\t')\n",
        "\n",
        "# Load test data\n",
        "abstracts_test = pd.read_csv(data_path + 'abstracts_test.csv', sep='\\t')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BqOF1fYyIPFt",
        "outputId": "fa404fc5-67b3-4a13-918c-e3cfb864d1f3"
      },
      "source": [
        "# print dimensions of data\n",
        "print('Dimension of abstracts train: ', abstracts_train.shape)\n",
        "print('Dimension of entities train: ', entities_train.shape)\n",
        "print()\n",
        "print('Dimension of abstracts test: ', abstracts_test.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dimension of abstracts train:  (400, 3)\n",
            "Dimension of entities train:  (13636, 7)\n",
            "\n",
            "Dimension of abstracts test:  (100, 3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VNiLHfqbIMhr"
      },
      "source": [
        "## EDA"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        },
        "id": "gg0W9u6cINCi",
        "outputId": "d40fd02b-2e8c-4e33-b067-3db538380185"
      },
      "source": [
        "abstracts_train.info()\n",
        "abstracts_train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 400 entries, 0 to 399\n",
            "Data columns (total 3 columns):\n",
            " #   Column       Non-Null Count  Dtype \n",
            "---  ------       --------------  ----- \n",
            " 0   abstract_id  400 non-null    int64 \n",
            " 1   title        400 non-null    object\n",
            " 2   abstract     400 non-null    object\n",
            "dtypes: int64(1), object(2)\n",
            "memory usage: 9.5+ KB\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>abstract_id</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1353340</td>\n",
              "      <td>Late-onset metachromatic leukodystrophy: molec...</td>\n",
              "      <td>We report on a new allele at the arylsulfatase...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1671881</td>\n",
              "      <td>Two distinct mutations at a single BamHI site ...</td>\n",
              "      <td>Classical phenylketonuria is an autosomal rece...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1848636</td>\n",
              "      <td>Debrisoquine phenotype and the pharmacokinetic...</td>\n",
              "      <td>The metabolism of the cardioselective beta-blo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2422478</td>\n",
              "      <td>Midline B3 serotonin nerves in rat medulla are...</td>\n",
              "      <td>Previous experiments in this laboratory have s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2491010</td>\n",
              "      <td>Molecular and phenotypic analysis of patients ...</td>\n",
              "      <td>Eighty unrelated individuals with Duchenne mus...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "   abstract_id  ...                                           abstract\n",
              "0      1353340  ...  We report on a new allele at the arylsulfatase...\n",
              "1      1671881  ...  Classical phenylketonuria is an autosomal rece...\n",
              "2      1848636  ...  The metabolism of the cardioselective beta-blo...\n",
              "3      2422478  ...  Previous experiments in this laboratory have s...\n",
              "4      2491010  ...  Eighty unrelated individuals with Duchenne mus...\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
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    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "W411UpEnJcjU",
        "outputId": "a5c4f8f6-3c7d-46c2-c496-eef50499e65f"
      },
      "source": [
        "entities_train.info()\n",
        "entities_train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 13636 entries, 0 to 13635\n",
            "Data columns (total 7 columns):\n",
            " #   Column         Non-Null Count  Dtype \n",
            "---  ------         --------------  ----- \n",
            " 0   id             13636 non-null  int64 \n",
            " 1   abstract_id    13636 non-null  int64 \n",
            " 2   offset_start   13636 non-null  int64 \n",
            " 3   offset_finish  13636 non-null  int64 \n",
            " 4   type           13636 non-null  object\n",
            " 5   mention        13636 non-null  object\n",
            " 6   entity_ids     13636 non-null  object\n",
            "dtypes: int64(4), object(3)\n",
            "memory usage: 745.8+ KB\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>abstract_id</th>\n",
              "      <th>offset_start</th>\n",
              "      <th>offset_finish</th>\n",
              "      <th>type</th>\n",
              "      <th>mention</th>\n",
              "      <th>entity_ids</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1353340</td>\n",
              "      <td>11</td>\n",
              "      <td>39</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>metachromatic leukodystrophy</td>\n",
              "      <td>D007966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1353340</td>\n",
              "      <td>111</td>\n",
              "      <td>126</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>arylsulfatase A</td>\n",
              "      <td>410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1353340</td>\n",
              "      <td>128</td>\n",
              "      <td>132</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>ARSA</td>\n",
              "      <td>410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1353340</td>\n",
              "      <td>159</td>\n",
              "      <td>187</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>metachromatic leukodystrophy</td>\n",
              "      <td>D007966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1353340</td>\n",
              "      <td>189</td>\n",
              "      <td>192</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>MLD</td>\n",
              "      <td>D007966</td>\n",
              "    </tr>\n",
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            "text/plain": [
              "   id  abstract_id  ...                       mention  entity_ids\n",
              "0   0      1353340  ...  metachromatic leukodystrophy     D007966\n",
              "1   1      1353340  ...               arylsulfatase A         410\n",
              "2   2      1353340  ...                          ARSA         410\n",
              "3   3      1353340  ...  metachromatic leukodystrophy     D007966\n",
              "4   4      1353340  ...                           MLD     D007966\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PAN9LPEYNqNc",
        "outputId": "e060ddbd-8c52-4ff5-a5f0-abffe560d81b"
      },
      "source": [
        "missing_cols(abstracts_train)\n",
        "missing_cols(entities_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "no missing values\n",
            "no missing values\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tKveqnOGYZuA"
      },
      "source": [
        "### How many types are there?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "FcA-mZ75NPa4",
        "outputId": "88f6d931-dbad-4816-82ee-8e61ee0b177b"
      },
      "source": [
        "entities_train['type'].value_counts().plot(kind=\"barh\").invert_yaxis();"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "wSanfdmd4EvF",
        "outputId": "a4a330db-6407-4811-c1d4-dac2ad175b51"
      },
      "source": [
        "abstracts_train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>abstract_id</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1353340</td>\n",
              "      <td>Late-onset metachromatic leukodystrophy: molec...</td>\n",
              "      <td>We report on a new allele at the arylsulfatase...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1671881</td>\n",
              "      <td>Two distinct mutations at a single BamHI site ...</td>\n",
              "      <td>Classical phenylketonuria is an autosomal rece...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1848636</td>\n",
              "      <td>Debrisoquine phenotype and the pharmacokinetic...</td>\n",
              "      <td>The metabolism of the cardioselective beta-blo...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2422478</td>\n",
              "      <td>Midline B3 serotonin nerves in rat medulla are...</td>\n",
              "      <td>Previous experiments in this laboratory have s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2491010</td>\n",
              "      <td>Molecular and phenotypic analysis of patients ...</td>\n",
              "      <td>Eighty unrelated individuals with Duchenne mus...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   abstract_id  ...                                           abstract\n",
              "0      1353340  ...  We report on a new allele at the arylsulfatase...\n",
              "1      1671881  ...  Classical phenylketonuria is an autosomal rece...\n",
              "2      1848636  ...  The metabolism of the cardioselective beta-blo...\n",
              "3      2422478  ...  Previous experiments in this laboratory have s...\n",
              "4      2491010  ...  Eighty unrelated individuals with Duchenne mus...\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2dVeUbLbBVuJ"
      },
      "source": [
        "## scispaCy in action"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HzZ657-UZDV3",
        "outputId": "1800fcbf-e47f-427a-a718-8e490071dd0c"
      },
      "source": [
        "text = abstracts_train.iloc[0].title + abstracts_train.iloc[0].abstract\n",
        "len(text)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "717"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "id": "AGmuRsUTZMKa",
        "outputId": "8c9f7da0-eae4-41c8-de74-4c5a2ad3cf9b"
      },
      "source": [
        "text"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'Late-onset metachromatic leukodystrophy: molecular pathology in two siblings.We report on a new allele at the arylsulfatase A (ARSA) locus causing late-onset metachromatic leukodystrophy (MLD). In that allele arginine84, a residue that is highly conserved in the arylsulfatase gene family, is replaced by glutamine. In contrast to alleles that cause early-onset MLD, the arginine84 to glutamine substitution is associated with some residual ARSA activity. A comparison of genotypes, ARSA activities, and clinical data on 4 individuals carrying the allele of 81 patients with MLD examined, further validates the concept that different degrees of residual ARSA activity are the basis of phenotypical variation in MLD.. '"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mMdDMA_pZmLC"
      },
      "source": [
        "nlp = en_ner_bionlp13cg_md.load()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M3lhnOpVBbc4"
      },
      "source": [
        "doc_bionlp13cg = nlp(text)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rjNHJCcpFaD2",
        "outputId": "3bc5731e-a5ff-419d-93e3-4bb4f06e7638"
      },
      "source": [
        "doc_bionlp13cg.ents"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(arylsulfatase A,\n",
              " ARSA),\n",
              " MLD,\n",
              " arginine84,\n",
              " arylsulfatase,\n",
              " glutamine,\n",
              " MLD,\n",
              " arginine84,\n",
              " glutamine,\n",
              " ARSA,\n",
              " ARSA,\n",
              " individuals,\n",
              " patients,\n",
              " MLD,\n",
              " ARSA,\n",
              " MLD)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "3JddQlpDBpR8",
        "outputId": "96b04753-1ac1-43be-f25a-7247960e34b3"
      },
      "source": [
        "displacy.render(doc_bionlp13cg_md, jupyter=True, style='ent')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">Late-onset metachromatic leukodystrophy: molecular pathology in two siblings.We report on a new allele at the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arylsulfatase A\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " (\n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA)\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " locus causing late-onset metachromatic leukodystrophy (\n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CANCER</span>\n",
              "</mark>\n",
              "). In that allele \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arginine84\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              ", a residue that is highly conserved in the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arylsulfatase\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " gene family, is replaced by \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    glutamine\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">AMINO_ACID</span>\n",
              "</mark>\n",
              ". In contrast to alleles that cause early-onset \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              ", the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arginine84\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " to \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    glutamine\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">AMINO_ACID</span>\n",
              "</mark>\n",
              " substitution is associated with some residual \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " activity. A comparison of genotypes, \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " activities, and clinical data on 4 \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    individuals\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORGANISM</span>\n",
              "</mark>\n",
              " carrying the allele of 81 \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    patients\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORGANISM</span>\n",
              "</mark>\n",
              " with \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " examined, further validates the concept that different degrees of residual \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              " activity are the basis of phenotypical variation in \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GENE_OR_GENE_PRODUCT</span>\n",
              "</mark>\n",
              ".. </div></span>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y_U4ckf6BsWb",
        "outputId": "853ffd64-e555-45af-bc64-7ad2041aac7a"
      },
      "source": [
        "pprint({(X.text, X.label_, X.start_char, X.end_char) for X in doc_bionlp13cg_md.ents})"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{('ARSA', 'GENE_OR_GENE_PRODUCT', 441, 445),\n",
            " ('ARSA', 'GENE_OR_GENE_PRODUCT', 483, 487),\n",
            " ('ARSA', 'GENE_OR_GENE_PRODUCT', 654, 658),\n",
            " ('ARSA)', 'GENE_OR_GENE_PRODUCT', 127, 132),\n",
            " ('MLD', 'CANCER', 188, 191),\n",
            " ('MLD', 'GENE_OR_GENE_PRODUCT', 362, 365),\n",
            " ('MLD', 'GENE_OR_GENE_PRODUCT', 575, 578),\n",
            " ('MLD', 'GENE_OR_GENE_PRODUCT', 711, 714),\n",
            " ('arginine84', 'GENE_OR_GENE_PRODUCT', 209, 219),\n",
            " ('arginine84', 'GENE_OR_GENE_PRODUCT', 371, 381),\n",
            " ('arylsulfatase', 'GENE_OR_GENE_PRODUCT', 263, 276),\n",
            " ('arylsulfatase A', 'GENE_OR_GENE_PRODUCT', 110, 125),\n",
            " ('glutamine', 'AMINO_ACID', 305, 314),\n",
            " ('glutamine', 'AMINO_ACID', 385, 394),\n",
            " ('individuals', 'ORGANISM', 523, 534),\n",
            " ('patients', 'ORGANISM', 561, 569)}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o_uHfhbgIHA7"
      },
      "source": [
        "### Use the three other models"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r9ow0FfyPxEc"
      },
      "source": [
        "nlp_craft = en_ner_craft_md.load()\n",
        "nlp_jnlpba = en_ner_jnlpba_md.load()\n",
        "nlp_bc5cdr = en_ner_bc5cdr_md.load()\n",
        "\n",
        "doc_craft = nlp_craft(text)\n",
        "doc_jnlpba = nlp_jnlpba(text)\n",
        "doc_bc5cdr= nlp_bc5cdr(text)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4PNKMsTwBb6P"
      },
      "source": [
        "## Display the entities with other models"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 227
        },
        "id": "FL5mU3EOwLCL",
        "outputId": "c4b65b23-f1d5-433f-a2cd-c504422424d3"
      },
      "source": [
        "displacy.render(doc_craft, jupyter=True, style='ent')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">Late-onset metachromatic leukodystrophy: \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    molecular\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CHEBI</span>\n",
              "</mark>\n",
              " pathology in two siblings.We report on a new \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    allele\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " at the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arylsulfatase A\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GGP</span>\n",
              "</mark>\n",
              " (ARSA) \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    locus\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " causing late-onset metachromatic leukodystrophy (MLD). In that \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    allele\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " arginine84, a residue that is highly \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    conserved\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " in the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arylsulfatase gene\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GGP</span>\n",
              "</mark>\n",
              " family, is \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    replaced\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " by \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    glutamine\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CHEBI</span>\n",
              "</mark>\n",
              ". In contrast to \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    alleles\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " that cause early-onset MLD, the arginine84 to \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    glutamine substitution\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CHEBI</span>\n",
              "</mark>\n",
              " is associated with some residual ARSA activity. A comparison of \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    genotypes\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              ", \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GGP</span>\n",
              "</mark>\n",
              " activities, and clinical data on 4 \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    individuals\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">TAXON</span>\n",
              "</mark>\n",
              " carrying the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    allele\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">SO</span>\n",
              "</mark>\n",
              " of 81 patients with MLD examined, further validates the concept that different degrees of residual ARSA activity are the basis of phenotypical variation in MLD.. </div></span>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 227
        },
        "id": "3_lCblMSxPsU",
        "outputId": "bc4b373d-35fc-42fc-9833-beca702b2238"
      },
      "source": [
        "displacy.render(doc_jnlpba, jupyter=True, style='ent')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">Late-onset metachromatic leukodystrophy: molecular pathology in two siblings.We report on a new \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    allele\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DNA</span>\n",
              "</mark>\n",
              " at the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arylsulfatase A (ARSA) locus\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DNA</span>\n",
              "</mark>\n",
              " causing late-onset metachromatic leukodystrophy (MLD). In that \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    allele arginine84\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DNA</span>\n",
              "</mark>\n",
              ", a residue that is highly conserved in the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arylsulfatase gene family\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DNA</span>\n",
              "</mark>\n",
              ", is replaced by glutamine. In contrast to alleles that cause early-onset MLD, the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    arginine84\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PROTEIN</span>\n",
              "</mark>\n",
              " to glutamine substitution is associated with some residual \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PROTEIN</span>\n",
              "</mark>\n",
              " activity. A comparison of genotypes, \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PROTEIN</span>\n",
              "</mark>\n",
              " activities, and clinical data on 4 individuals carrying the \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    allele\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DNA</span>\n",
              "</mark>\n",
              " of 81 patients with MLD examined, further validates the concept that different degrees of residual \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    ARSA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PROTEIN</span>\n",
              "</mark>\n",
              " activity are the basis of phenotypical variation in MLD.. </div></span>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 227
        },
        "id": "DKvnI_c-xQcd",
        "outputId": "d7d0448d-671a-46d0-c9ec-14f2d9691928"
      },
      "source": [
        "displacy.render(doc_bc5cdr, jupyter=True, style='ent')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    Late-onset metachromatic leukodystrophy\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DISEASE</span>\n",
              "</mark>\n",
              ": molecular pathology in two siblings.We report on a new allele at the arylsulfatase A (ARSA) locus causing \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    late-onset metachromatic leukodystrophy\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DISEASE</span>\n",
              "</mark>\n",
              " (\n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DISEASE</span>\n",
              "</mark>\n",
              "). In that allele arginine84, a residue that is highly conserved in the arylsulfatase gene family, is replaced by \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    glutamine\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CHEMICAL</span>\n",
              "</mark>\n",
              ". In contrast to alleles that cause early-onset \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DISEASE</span>\n",
              "</mark>\n",
              ", the arginine84 to \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    glutamine\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CHEMICAL</span>\n",
              "</mark>\n",
              " substitution is associated with some residual ARSA activity. A comparison of genotypes, ARSA activities, and clinical data on 4 individuals carrying the allele of 81 patients with \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DISEASE</span>\n",
              "</mark>\n",
              " examined, further validates the concept that different degrees of residual ARSA activity are the basis of phenotypical variation in \n",
              "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    MLD\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DISEASE</span>\n",
              "</mark>\n",
              ".. </div></span>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w_GrVSoeMeEx"
      },
      "source": [
        "Let's take the above entitiy categorizations and put them into data frame"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DppGsxOfQb__"
      },
      "source": [
        "data_doc_bionlp13cg = [(X.text, X.label_, X.start_char, X.end_char) for X in doc_bionlp13cg.ents]\n",
        "data_doc_craft = [(X.text, X.label_, X.start_char, X.end_char) for X in doc_craft.ents]\n",
        "data_doc_bc5cdr = [(X.text, X.label_, X.start_char, X.end_char) for X in doc_bc5cdr.ents]\n",
        "data_doc_jnlpba = [(X.text, X.label_, X.start_char, X.end_char) for X in doc_jnlpba.ents]\n",
        "\n",
        "data = data_doc_bionlp13cg + data_doc_craft + data_doc_bc5cdr + data_doc_jnlpba"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pf2YmV76by3_",
        "outputId": "25c05811-279f-4804-f4dc-517064fb2fa4"
      },
      "source": [
        "len(data)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "48"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jRFL_GzHNioB"
      },
      "source": [
        "attrs = [\"text\", \"label_\", \"start_char\", \"end_char\"]\n",
        "temp_df = pd.DataFrame(data, columns=attrs)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "jwgMssK8VUT1",
        "outputId": "e3294a55-31de-46f7-b4d8-dcd231a20cf2"
      },
      "source": [
        "temp_train_df = entities_train.query('abstract_id == 1353340')\n",
        "temp_train_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>abstract_id</th>\n",
              "      <th>offset_start</th>\n",
              "      <th>offset_finish</th>\n",
              "      <th>type</th>\n",
              "      <th>mention</th>\n",
              "      <th>entity_ids</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1353340</td>\n",
              "      <td>11</td>\n",
              "      <td>39</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>metachromatic leukodystrophy</td>\n",
              "      <td>D007966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1353340</td>\n",
              "      <td>111</td>\n",
              "      <td>126</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>arylsulfatase A</td>\n",
              "      <td>410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1353340</td>\n",
              "      <td>128</td>\n",
              "      <td>132</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>ARSA</td>\n",
              "      <td>410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1353340</td>\n",
              "      <td>159</td>\n",
              "      <td>187</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>metachromatic leukodystrophy</td>\n",
              "      <td>D007966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1353340</td>\n",
              "      <td>189</td>\n",
              "      <td>192</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>MLD</td>\n",
              "      <td>D007966</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  abstract_id  ...                       mention  entity_ids\n",
              "0   0      1353340  ...  metachromatic leukodystrophy     D007966\n",
              "1   1      1353340  ...               arylsulfatase A         410\n",
              "2   2      1353340  ...                          ARSA         410\n",
              "3   3      1353340  ...  metachromatic leukodystrophy     D007966\n",
              "4   4      1353340  ...                           MLD     D007966\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "NHTgQm9Fe-fq",
        "outputId": "f9499838-1963-4458-f696-2aa3fa038e83"
      },
      "source": [
        "merged_df = temp_df.merge(temp_train_df, how = 'inner', left_on ='text', right_on = 'mention')\n",
        "merged_df[['text', 'label_', 'type']].drop_duplicates()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>label_</th>\n",
              "      <th>type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>arylsulfatase A</td>\n",
              "      <td>GENE_OR_GENE_PRODUCT</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>arylsulfatase A</td>\n",
              "      <td>GGP</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>MLD</td>\n",
              "      <td>CANCER</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>MLD</td>\n",
              "      <td>GENE_OR_GENE_PRODUCT</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>MLD</td>\n",
              "      <td>DISEASE</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>arginine84</td>\n",
              "      <td>GENE_OR_GENE_PRODUCT</td>\n",
              "      <td>SequenceVariant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>arginine84</td>\n",
              "      <td>PROTEIN</td>\n",
              "      <td>SequenceVariant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>arylsulfatase</td>\n",
              "      <td>GENE_OR_GENE_PRODUCT</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>ARSA</td>\n",
              "      <td>GENE_OR_GENE_PRODUCT</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>ARSA</td>\n",
              "      <td>GGP</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>ARSA</td>\n",
              "      <td>PROTEIN</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>patients</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>OrganismTaxon</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               text                label_                        type\n",
              "0   arylsulfatase A  GENE_OR_GENE_PRODUCT           GeneOrGeneProduct\n",
              "1   arylsulfatase A                   GGP           GeneOrGeneProduct\n",
              "2               MLD                CANCER  DiseaseOrPhenotypicFeature\n",
              "6               MLD  GENE_OR_GENE_PRODUCT  DiseaseOrPhenotypicFeature\n",
              "18              MLD               DISEASE  DiseaseOrPhenotypicFeature\n",
              "34       arginine84  GENE_OR_GENE_PRODUCT             SequenceVariant\n",
              "36       arginine84               PROTEIN             SequenceVariant\n",
              "37    arylsulfatase  GENE_OR_GENE_PRODUCT           GeneOrGeneProduct\n",
              "38             ARSA  GENE_OR_GENE_PRODUCT           GeneOrGeneProduct\n",
              "50             ARSA                   GGP           GeneOrGeneProduct\n",
              "54             ARSA               PROTEIN           GeneOrGeneProduct\n",
              "66         patients              ORGANISM               OrganismTaxon"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6ipXny6ogSYt",
        "outputId": "5cfa7ffe-df15-4110-a9b0-eb86d7e4320f"
      },
      "source": [
        "temp_df.label_.unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['GENE_OR_GENE_PRODUCT', 'CANCER', 'AMINO_ACID', 'ORGANISM',\n",
              "       'CHEBI', 'SO', 'GGP', 'TAXON', 'DISEASE', 'CHEMICAL', 'DNA',\n",
              "       'PROTEIN'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5QR1mvIPjlQz",
        "outputId": "151d8e37-194f-4261-ed0d-77c284647ff2"
      },
      "source": [
        "temp_train_df.type.unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['DiseaseOrPhenotypicFeature', 'GeneOrGeneProduct',\n",
              "       'SequenceVariant', 'OrganismTaxon'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UkJTBSbBeFd5"
      },
      "source": [
        "temp_df.label_ = temp_df.label_.map(\n",
        "    {\n",
        "        \"GENE_OR_GENE_PRODUCT\": \"GeneOrGeneProduct\",\n",
        "        \"GGP\": \"GeneOrGeneProduct\",\n",
        "        \"ORGANISM\": \"OrganismTaxon\",\n",
        "        \"CANCER\": \"DiseaseOrPhenotypicFeature\",\n",
        "        \"DISEASE\": \"DiseaseOrPhenotypicFeature\",\n",
        "        \"CHEBI\": \"ChemicalEntity\",\n",
        "        \"CHEMICAL\": \"ChemicalEntity\",\n",
        "        \"PROTEIN\": \"SequenceVariant\",\n",
        "        \"AMINO_ACID\": \"SequenceVariant\",\n",
        "        \"SO\": \"SO\",\n",
        "        \"TAXON\": \"TAXON\",\n",
        "        \"DNA\": \"DNA\",\n",
        "    }\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "OSGhfw6ejNId",
        "outputId": "47f506cd-276e-4ccf-8d2c-cabf1d641ea2"
      },
      "source": [
        "temp_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>label_</th>\n",
              "      <th>start_char</th>\n",
              "      <th>end_char</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>arylsulfatase A</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>110</td>\n",
              "      <td>125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ARSA)</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>127</td>\n",
              "      <td>132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>MLD</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>188</td>\n",
              "      <td>191</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>arginine84</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>209</td>\n",
              "      <td>219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>arylsulfatase</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>263</td>\n",
              "      <td>276</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              text                      label_  start_char  end_char\n",
              "0  arylsulfatase A           GeneOrGeneProduct         110       125\n",
              "1            ARSA)           GeneOrGeneProduct         127       132\n",
              "2              MLD  DiseaseOrPhenotypicFeature         188       191\n",
              "3       arginine84           GeneOrGeneProduct         209       219\n",
              "4    arylsulfatase           GeneOrGeneProduct         263       276"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NXhPmplRjdOO"
      },
      "source": [
        "temp_df['start_char'] = temp_df['start_char'] + 1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZfxzPxqpj3Mv"
      },
      "source": [
        "temp_df.text = temp_df.text.str.replace(')', '')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "lSX87SatjoIX",
        "outputId": "9f9516c3-ebe4-46b5-d8b3-4265c5fc8e54"
      },
      "source": [
        "temp_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>label_</th>\n",
              "      <th>start_char</th>\n",
              "      <th>end_char</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>arylsulfatase A</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>111</td>\n",
              "      <td>125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ARSA</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>128</td>\n",
              "      <td>132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>MLD</td>\n",
              "      <td>DiseaseOrPhenotypicFeature</td>\n",
              "      <td>189</td>\n",
              "      <td>191</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>arginine84</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>210</td>\n",
              "      <td>219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>arylsulfatase</td>\n",
              "      <td>GeneOrGeneProduct</td>\n",
              "      <td>264</td>\n",
              "      <td>276</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              text                      label_  start_char  end_char\n",
              "0  arylsulfatase A           GeneOrGeneProduct         111       125\n",
              "1             ARSA           GeneOrGeneProduct         128       132\n",
              "2              MLD  DiseaseOrPhenotypicFeature         189       191\n",
              "3       arginine84           GeneOrGeneProduct         210       219\n",
              "4    arylsulfatase           GeneOrGeneProduct         264       276"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    }
  ]
}