Spacy_Custom_NER_Youtube.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Spacy Custom NER: Youtube.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyO6NRL7LBHCAxSowKqJbuQ2",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/PradipNichite/Youtube-Tutorials/blob/main/Spacy_Custom_NER_Youtube.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Building Custom Named Entity Recognition Model Using Spacy**"
      ],
      "metadata": {
        "id": "2NdRitT8329p"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://newscatcherapi.com/blog/train-custom-named-entity-recognition-ner-model-with-spacy-v3"
      ],
      "metadata": {
        "id": "Xh_gXGxU2bwE"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FFOiNNeP0giN"
      },
      "outputs": [],
      "source": [
        "import spacy"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !python -m spacy download en_core_web_sm\n",
        "!python -m spacy download en_core_web_lg"
      ],
      "metadata": {
        "id": "enIOTr8y6hf9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nlp = spacy.load(\"en_core_web_lg\")\n",
        "nlp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GGlQY8Ro2hw6",
        "outputId": "ff0fe75c-6a0c-4260-9e99-ee08bcf8a6e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<spacy.lang.en.English at 0x7fbc20fcb050>"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "doc = nlp(\"Donad Trump was President of USA\")"
      ],
      "metadata": {
        "id": "uGingzbmvgnL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "doc"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OFPOI7gY-ha4",
        "outputId": "b5177348-0e91-4344-ba8d-bf6161f07d3f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Donad Trump was President of USA"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(doc)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NWrodKDk-jwc",
        "outputId": "4ece91e5-4ce1-49e3-8f62-fc55602c9a62"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "spacy.tokens.doc.Doc"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "doc.ents"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y7WS3fl38D_0",
        "outputId": "fdf602f3-6db8-43f3-fef8-254f9a103a69"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(Donad Trump, USA)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "doc.ents[0], type(doc.ents[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AovSOSmKvlz9",
        "outputId": "2f8d3d7a-4cdb-4e0b-ce92-34cbac8673a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(Donad Trump, spacy.tokens.span.Span)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from spacy import displacy\n",
        "displacy.render(doc, style=\"ent\", jupyter=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "id": "5ou7-MtW8gXW",
        "outputId": "270927a3-227e-4c79-b2a9-d0550abdc77f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
              "<mark class=\"entity\" style=\"background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    Donad Trump\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PERSON</span>\n",
              "</mark>\n",
              " was President of \n",
              "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    USA\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
              "</mark>\n",
              "</div></span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import json\n",
        "# https://www.kaggle.com/datasets/finalepoch/medical-ner \n",
        "with open('/content/Corona2.json', 'r') as f:\n",
        "    data = json.load(f)"
      ],
      "metadata": {
        "id": "_QIeRdwg21l6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data['examples'][0]"
      ],
      "metadata": {
        "id": "GtksxtBq3y1i"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data['examples'][0].keys()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cPWB_Mko4OiP",
        "outputId": "e40721fb-8cff-4e54-fe77-738a924468f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_keys(['id', 'content', 'metadata', 'annotations', 'classifications'])"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['examples'][0]['content']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 182
        },
        "id": "v9cdB6C99Jym",
        "outputId": "2c68f931-cd3e-4218-e252-223e444dbd7b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"While bismuth compounds (Pepto-Bismol) decreased the number of bowel movements in those with travelers' diarrhea, they do not decrease the length of illness.[91] Anti-motility agents like loperamide are also effective at reducing the number of stools but not the duration of disease.[8] These agents should be used only if bloody diarrhea is not present.[92]\\n\\nDiosmectite, a natural aluminomagnesium silicate clay, is effective in alleviating symptoms of acute diarrhea in children,[93] and also has some effects in chronic functional diarrhea, radiation-induced diarrhea, and chemotherapy-induced diarrhea.[45] Another absorbent agent used for the treatment of mild diarrhea is kaopectate.\\n\\nRacecadotril an antisecretory medication may be used to treat diarrhea in children and adults.[86] It has better tolerability than loperamide, as it causes less constipation and flatulence.[94]\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['examples'][0]['annotations'][0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uQbKf0Ry9Opx",
        "outputId": "ef77fa40-1e4e-4321-fa8b-063d2131fa0b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'correct': None,\n",
              " 'end': 371,\n",
              " 'example_id': '18c2f619-f102-452f-ab81-d26f7e283ffe',\n",
              " 'human_annotations': [{'annotator_id': 1,\n",
              "   'name': 'Ashpat123',\n",
              "   'reason': 'exploration',\n",
              "   'tagged_token_id': '0825a1bf-6a6e-4fa2-be77-8d104701eaed',\n",
              "   'timestamp': '2020-03-21T00:24:32.098000Z'}],\n",
              " 'id': '0825a1bf-6a6e-4fa2-be77-8d104701eaed',\n",
              " 'model_annotations': [],\n",
              " 'start': 360,\n",
              " 'tag_id': 'c06bd022-6ded-44a5-8d90-f17685bb85a1',\n",
              " 'tag_name': 'Medicine',\n",
              " 'value': 'Diosmectite'}"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_data = []\n",
        "for example in data['examples']:\n",
        "  temp_dict = {}\n",
        "  temp_dict['text'] = example['content']\n",
        "  temp_dict['entities'] = []\n",
        "  for annotation in example['annotations']:\n",
        "    start = annotation['start']\n",
        "    end = annotation['end']\n",
        "    label = annotation['tag_name'].upper()\n",
        "    temp_dict['entities'].append((start, end, label))\n",
        "  training_data.append(temp_dict)\n",
        "  \n",
        "print(training_data[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gXS3_RsQ3PuP",
        "outputId": "f8a2a2f6-ea0b-427b-9da3-f564a195acce"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'text': \"While bismuth compounds (Pepto-Bismol) decreased the number of bowel movements in those with travelers' diarrhea, they do not decrease the length of illness.[91] Anti-motility agents like loperamide are also effective at reducing the number of stools but not the duration of disease.[8] These agents should be used only if bloody diarrhea is not present.[92]\\n\\nDiosmectite, a natural aluminomagnesium silicate clay, is effective in alleviating symptoms of acute diarrhea in children,[93] and also has some effects in chronic functional diarrhea, radiation-induced diarrhea, and chemotherapy-induced diarrhea.[45] Another absorbent agent used for the treatment of mild diarrhea is kaopectate.\\n\\nRacecadotril an antisecretory medication may be used to treat diarrhea in children and adults.[86] It has better tolerability than loperamide, as it causes less constipation and flatulence.[94]\", 'entities': [(360, 371, 'MEDICINE'), (383, 408, 'MEDICINE'), (104, 112, 'MEDICALCONDITION'), (679, 689, 'MEDICINE'), (6, 23, 'MEDICINE'), (25, 37, 'MEDICINE'), (461, 470, 'MEDICALCONDITION'), (577, 589, 'MEDICINE'), (853, 865, 'MEDICALCONDITION'), (188, 198, 'MEDICINE'), (754, 762, 'MEDICALCONDITION'), (870, 880, 'MEDICALCONDITION'), (823, 833, 'MEDICINE'), (852, 853, 'MEDICALCONDITION'), (461, 469, 'MEDICALCONDITION'), (535, 543, 'MEDICALCONDITION'), (692, 704, 'MEDICINE'), (563, 571, 'MEDICALCONDITION')]}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_data[0]['text']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 182
        },
        "id": "oOvb8JZI3doC",
        "outputId": "3ccd930d-a1d4-4f28-d3c6-6f957ec6414c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"While bismuth compounds (Pepto-Bismol) decreased the number of bowel movements in those with travelers' diarrhea, they do not decrease the length of illness.[91] Anti-motility agents like loperamide are also effective at reducing the number of stools but not the duration of disease.[8] These agents should be used only if bloody diarrhea is not present.[92]\\n\\nDiosmectite, a natural aluminomagnesium silicate clay, is effective in alleviating symptoms of acute diarrhea in children,[93] and also has some effects in chronic functional diarrhea, radiation-induced diarrhea, and chemotherapy-induced diarrhea.[45] Another absorbent agent used for the treatment of mild diarrhea is kaopectate.\\n\\nRacecadotril an antisecretory medication may be used to treat diarrhea in children and adults.[86] It has better tolerability than loperamide, as it causes less constipation and flatulence.[94]\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_data[0]['entities']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a1vLiWdK3ma6",
        "outputId": "d3f4d933-ce49-4ba2-f710-9e1144b98549"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(360, 371, 'MEDICINE'),\n",
              " (383, 408, 'MEDICINE'),\n",
              " (104, 112, 'MEDICALCONDITION'),\n",
              " (679, 689, 'MEDICINE'),\n",
              " (6, 23, 'MEDICINE'),\n",
              " (25, 37, 'MEDICINE'),\n",
              " (461, 470, 'MEDICALCONDITION'),\n",
              " (577, 589, 'MEDICINE'),\n",
              " (853, 865, 'MEDICALCONDITION'),\n",
              " (188, 198, 'MEDICINE'),\n",
              " (754, 762, 'MEDICALCONDITION'),\n",
              " (870, 880, 'MEDICALCONDITION'),\n",
              " (823, 833, 'MEDICINE'),\n",
              " (852, 853, 'MEDICALCONDITION'),\n",
              " (461, 469, 'MEDICALCONDITION'),\n",
              " (535, 543, 'MEDICALCONDITION'),\n",
              " (692, 704, 'MEDICINE'),\n",
              " (563, 571, 'MEDICALCONDITION')]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_data[0]['text'][360:371]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "vWYU8pQ83zmg",
        "outputId": "83456a72-e098-46f8-d2f8-b574c5cf74ed"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Diosmectite'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from spacy.tokens import DocBin\n",
        "from tqdm import tqdm\n",
        "\n",
        "nlp = spacy.blank(\"en\") # load a new spacy model\n",
        "doc_bin = DocBin()"
      ],
      "metadata": {
        "id": "ZrbrxWEi3qLJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from spacy.util import filter_spans\n",
        "\n",
        "for training_example  in tqdm(training_data): \n",
        "    text = training_example['text']\n",
        "    labels = training_example['entities']\n",
        "    doc = nlp.make_doc(text) \n",
        "    ents = []\n",
        "    for start, end, label in labels:\n",
        "        span = doc.char_span(start, end, label=label, alignment_mode=\"contract\")\n",
        "        if span is None:\n",
        "            print(\"Skipping entity\")\n",
        "        else:\n",
        "            ents.append(span)\n",
        "    filtered_ents = filter_spans(ents)\n",
        "    doc.ents = filtered_ents \n",
        "    doc_bin.add(doc)\n",
        "\n",
        "doc_bin.to_disk(\"train.spacy\") "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jBd4mdq039Ag",
        "outputId": "ef5f11c3-96c7-47f9-e6ed-9f7c46ad15d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 31/31 [00:00<00:00, 335.64it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n",
            "Skipping entity\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# https://spacy.io/usage/training#quickstart"
      ],
      "metadata": {
        "id": "0AqYeEoS4avo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!python -m spacy init fill-config base_config.cfg config.cfg"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gyg-6DXU5Dhu",
        "outputId": "11985c14-3f6d-4d19-bbd0-201029a4f2b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[38;5;2m✔ Auto-filled config with all values\u001b[0m\n",
            "\u001b[38;5;2m✔ Saved config\u001b[0m\n",
            "config.cfg\n",
            "You can now add your data and train your pipeline:\n",
            "python -m spacy train config.cfg --paths.train ./train.spacy --paths.dev ./dev.spacy\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python -m spacy train config.cfg --output ./ --paths.train ./train.spacy --paths.dev ./train.spacy "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xwoa711K5GuG",
        "outputId": "acd35773-8c1f-4732-faa7-e626dcf3db8b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[38;5;4mℹ Saving to output directory: .\u001b[0m\n",
            "\u001b[38;5;4mℹ Using CPU\u001b[0m\n",
            "\u001b[1m\n",
            "=========================== Initializing pipeline ===========================\u001b[0m\n",
            "[2022-07-01 18:31:37,021] [INFO] Set up nlp object from config\n",
            "[2022-07-01 18:31:37,041] [INFO] Pipeline: ['tok2vec', 'ner']\n",
            "[2022-07-01 18:31:37,047] [INFO] Created vocabulary\n",
            "[2022-07-01 18:31:40,116] [INFO] Added vectors: en_core_web_lg\n",
            "[2022-07-01 18:31:43,239] [INFO] Finished initializing nlp object\n",
            "[2022-07-01 18:31:45,876] [INFO] Initialized pipeline components: ['tok2vec', 'ner']\n",
            "\u001b[38;5;2m✔ Initialized pipeline\u001b[0m\n",
            "\u001b[1m\n",
            "============================= Training pipeline =============================\u001b[0m\n",
            "\u001b[38;5;4mℹ Pipeline: ['tok2vec', 'ner']\u001b[0m\n",
            "\u001b[38;5;4mℹ Initial learn rate: 0.001\u001b[0m\n",
            "E    #       LOSS TOK2VEC  LOSS NER  ENTS_F  ENTS_P  ENTS_R  SCORE \n",
            "---  ------  ------------  --------  ------  ------  ------  ------\n",
            "  0       0          0.00    153.29    0.49    0.64    0.39    0.00\n",
            "  7     200        501.32   3113.23   78.43   78.12   78.74    0.78\n",
            "\u001b[38;5;2m✔ Saved pipeline to output directory\u001b[0m\n",
            "model-last\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nlp_ner = spacy.load(\"model-best\")"
      ],
      "metadata": {
        "id": "uYfhbE013Hmh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "doc = nlp_ner(\"While bismuth compounds (Pepto-Bismol) decreased the number of bowel movements in those with travelers' diarrhea, they do not decrease the length of illness.[91] Anti-motility agents like loperamide are also effective at reducing the number of stools but not the duration of disease.[8] These agents should be used only if bloody diarrhea is not present.\")\n",
        "\n",
        "colors = {\"PATHOGEN\": \"#F67DE3\", \"MEDICINE\": \"#7DF6D9\", \"MEDICALCONDITION\":\"#a6e22d\"}\n",
        "options = {\"colors\": colors} \n",
        "\n",
        "spacy.displacy.render(doc, style=\"ent\", options= options, jupyter=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 157
        },
        "id": "Fm4S7YXEhvow",
        "outputId": "411028d2-528d-421a-bdee-5b7370cd2bec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">While \n",
              "<mark class=\"entity\" style=\"background: #7DF6D9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    bismuth\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">MEDICINE</span>\n",
              "</mark>\n",
              " compounds (\n",
              "<mark class=\"entity\" style=\"background: #7DF6D9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    Pepto-\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">MEDICINE</span>\n",
              "</mark>\n",
              "Bismol) decreased the number of bowel movements in those with travelers' \n",
              "<mark class=\"entity\" style=\"background: #a6e22d; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    diarrhea\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">MEDICALCONDITION</span>\n",
              "</mark>\n",
              ", they do not decrease the length of illness.[91] Anti-motility agents like \n",
              "<mark class=\"entity\" style=\"background: #7DF6D9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
              "    loperamide\n",
              "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">MEDICINE</span>\n",
              "</mark>\n",
              " are also effective at reducing the number of stools but not the duration of disease.[8] These agents should be used only if bloody diarrhea is not present.</div></span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "4ymsOpJIh3CJ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}