NLP_PROJECT_TASK_1.ipynb

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      "name": "NLP_PROJECT_TASK_1_.ipynb",
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      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/ParvaShah/Template_Extraction_NLP/blob/master/NLP_PROJECT_TASK_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
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      "metadata": {
        "id": "04OZ6pEmm599",
        "colab_type": "code",
        "outputId": "62d7645d-fcad-4c37-bed1-9f58077e288c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "import spacy\n",
        "from spacy import displacy\n",
        "nlp = spacy.load(\"en_core_web_sm\")\n",
        "import nltk\n",
        "nltk.download('wordnet')\n",
        "from nltk.corpus import wordnet as wn"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1KCP__iLoy4x",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sentence = \"Steven Paul Jobs \\\n",
        "was an American business magnate and investor. He was the \\\n",
        "chairman, chief executive officer (CEO), and co-founder of Apple Inc.; \\\n",
        "chairman and majority shareholder of Pixar; a member of The Walt \\\n",
        "Disney Company's board of directors following its acquisition of \\\n",
        "Pixar; and the founder, chairman, and CEO of NeXT. \\\n",
        "\"\n",
        "doc_sent = nlp(sentence)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CPuuOzD6p3QI",
        "colab_type": "code",
        "outputId": "93e3ef5d-e96e-45ff-972a-0364c5d650e4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        }
      },
      "source": [
        "print('Input Sentence: ',doc_sent)\n",
        "print()\n",
        "for i,sent in enumerate(doc_sent.sents):\n",
        "  print(i,'Sentence: ',sent)\n",
        "  doc_token = nlp(str(sent))\n",
        "  tokens = [tokens for tokens in doc_token]\n",
        "  print('Tokens: ',tokens)\n",
        "  lemma = [tokens.lemma_ for tokens in doc_token ]\n",
        "  print('Lemmas: ',lemma)\n",
        "  pos = [tokens.pos_ for tokens in doc_token ]\n",
        "  print('POS: ',pos)\n",
        "  dep = [tokens.dep_ for tokens in doc_token ]\n",
        "  print('DEP: ',dep)\n",
        "  hypernyms_list = []\n",
        "  for token in tokens:\n",
        "    tmp = []\n",
        "    for ss in wn.synsets(token.text):\n",
        "        if ss.hypernyms():\n",
        "            tmp.append(ss.hypernyms()[0].name()[:-5])\n",
        "    hypernyms_list.append(tmp)\n",
        "  print('Hypernymy: ',hypernyms_list)\n",
        "  \n",
        "  hyponyms_list = []\n",
        "  for token in tokens:\n",
        "    tmp = []\n",
        "    for ss in wn.synsets(token.text):\n",
        "        if ss.hyponyms():\n",
        "            tmp.append(ss.hyponyms()[0].name()[:-5])\n",
        "    hyponyms_list.append(tmp)\n",
        "  print('Hyponyms: ',hyponyms_list)\n",
        "\n",
        "  meronyms_list = []\n",
        "  for token in tokens:\n",
        "    tmp = []\n",
        "    for ss in wn.synsets(token.text):\n",
        "        if ss.part_meronyms():\n",
        "            tmp.append(ss.part_meronyms()[0].name()[:-5])\n",
        "    meronyms_list.append(tmp)\n",
        "  print('Meronyms: ',meronyms_list)\n",
        "  \n",
        "  holonyms_list = []\n",
        "  for token in tokens:\n",
        "    tmp = []\n",
        "    for ss in wn.synsets(token.text):\n",
        "        if ss.part_holonyms():\n",
        "            tmp.append(ss.part_holonyms()[0].name()[:-5])\n",
        "    holonyms_list.append(tmp)\n",
        "  print('Holonyms: ',holonyms_list)\n",
        "  \n",
        "  print()\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
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          "text": [
            "Input Sentence:  Steven Paul Jobs was an American business magnate and investor. He was the chairman, chief executive officer (CEO), and co-founder of Apple Inc.; chairman and majority shareholder of Pixar; a member of The Walt Disney Company's board of directors following its acquisition of Pixar; and the founder, chairman, and CEO of NeXT. \n",
            "\n",
            "0 Sentence:  Steven Paul Jobs was an American business magnate and investor.\n",
            "Tokens:  [Steven, Paul, Jobs, was, an, American, business, magnate, and, investor, .]\n",
            "Lemmas:  ['Steven', 'Paul', 'Jobs', 'be', 'an', 'american', 'business', 'magnate', 'and', 'investor', '.']\n",
            "POS:  ['PROPN', 'PROPN', 'PROPN', 'AUX', 'DET', 'ADJ', 'NOUN', 'NOUN', 'CCONJ', 'NOUN', 'PUNCT']\n",
            "DEP:  ['compound', 'compound', 'nsubj', 'ROOT', 'det', 'amod', 'compound', 'attr', 'cc', 'conj', 'punct']\n",
            "Hypernymy:  [[], [], ['activity', 'duty', 'workplace', 'product', 'duty', 'work', 'work', 'difficulty', 'unfortunate', 'application', 'robbery', 'cheat', 'hire', 'work', 'invest'], ['typify', 'take', 'stay', 'be'], ['associate_degree'], ['inhabitant', 'english', 'inhabitant'], ['enterprise', 'commerce', 'activity', 'concern', 'aim', 'business_activity', 'sector', 'people', 'acting'], ['businessman'], [], ['capitalist'], []]\n",
            "Hyponyms:  [[], [], ['accountancy', 'ball-buster', 'balance-of-payments_problem', 'bull'], ['abound', 'attend', 'coexist', 'equate', 'compose', 'cox', 'body', 'set_back'], [], ['african-american', 'african_american_vernacular_english', 'creole'], ['agency', 'advertising', 'accountancy', 'occasions', 'land-office_business', 'big_business', 'shtik'], ['oil_tycoon'], [], ['bear'], []]\n",
            "Meronyms:  [[], [], [], ['aberdeen'], [], [], ['business_activity'], [], [], [], []]\n",
            "Holonyms:  [[], [], ['hagiographa'], ['united_states'], [], [], ['market'], [], [], [], []]\n",
            "\n",
            "1 Sentence:  He was the chairman, chief executive officer (CEO), and co-founder of Apple Inc.; chairman and majority shareholder of Pixar; a member of The Walt Disney Company's board of directors following its acquisition of Pixar; and the founder, chairman, and CEO of NeXT.\n",
            "Tokens:  [He, was, the, chairman, ,, chief, executive, officer, (, CEO, ), ,, and, co, -, founder, of, Apple, Inc., ;, chairman, and, majority, shareholder, of, Pixar, ;, a, member, of, The, Walt, Disney, Company, 's, board, of, directors, following, its, acquisition, of, Pixar, ;, and, the, founder, ,, chairman, ,, and, CEO, of, NeXT, .]\n",
            "Lemmas:  ['-PRON-', 'be', 'the', 'chairman', ',', 'chief', 'executive', 'officer', '(', 'CEO', ')', ',', 'and', 'co', '-', 'founder', 'of', 'Apple', 'Inc.', ';', 'chairman', 'and', 'majority', 'shareholder', 'of', 'Pixar', ';', 'a', 'member', 'of', 'the', 'Walt', 'Disney', 'Company', \"'s\", 'board', 'of', 'director', 'follow', '-PRON-', 'acquisition', 'of', 'Pixar', ';', 'and', 'the', 'founder', ',', 'chairman', ',', 'and', 'CEO', 'of', 'NeXT', '.']\n",
            "POS:  ['PRON', 'AUX', 'DET', 'NOUN', 'PUNCT', 'ADJ', 'ADJ', 'NOUN', 'PUNCT', 'PROPN', 'PUNCT', 'PUNCT', 'CCONJ', 'NOUN', 'NOUN', 'NOUN', 'ADP', 'PROPN', 'PROPN', 'PUNCT', 'NOUN', 'CCONJ', 'NOUN', 'NOUN', 'ADP', 'PROPN', 'PUNCT', 'DET', 'NOUN', 'ADP', 'DET', 'PROPN', 'PROPN', 'PROPN', 'PART', 'NOUN', 'ADP', 'NOUN', 'VERB', 'DET', 'NOUN', 'ADP', 'PROPN', 'PUNCT', 'CCONJ', 'DET', 'NOUN', 'PUNCT', 'NOUN', 'PUNCT', 'CCONJ', 'PROPN', 'ADP', 'PROPN', 'PUNCT']\n",
            "DEP:  ['nsubj', 'ROOT', 'det', 'attr', 'punct', 'amod', 'amod', 'appos', 'punct', 'appos', 'punct', 'punct', 'cc', 'dep', 'dep', 'conj', 'prep', 'compound', 'pobj', 'punct', 'appos', 'cc', 'compound', 'conj', 'prep', 'pobj', 'punct', 'det', 'appos', 'prep', 'det', 'compound', 'compound', 'poss', 'case', 'pobj', 'prep', 'pobj', 'prep', 'poss', 'dobj', 'prep', 'pobj', 'punct', 'cc', 'det', 'conj', 'punct', 'appos', 'punct', 'cc', 'conj', 'prep', 'pobj', 'punct']\n",
            "Hypernymy:  [['chemical_element', 'letter'], ['typify', 'take', 'stay', 'be'], [], ['presiding_officer', 'head'], [], ['leader', 'supervisor', 'leader'], ['administrator', 'administration', 'head'], ['serviceman', 'holder', 'lawman', 'mariner', 'command'], [], ['corporate_executive'], [], [], [], ['monoxide', 'metallic_element', 'dissenter'], [], ['inflammation', 'originator', 'skilled_worker', 'fail', 'sink', 'change', 'stumble'], [], ['edible_fruit', 'apple_tree'], [], [], ['presiding_officer', 'head'], [], ['number', 'relative_quantity', 'age'], ['investor'], [], [], [], ['metric_linear_unit', 'fat-soluble_vitamin', 'nucleotide', 'purine', 'current_unit', 'letter', 'blood_group'], ['associate', 'part', 'external_body_part', 'unit', 'erectile_organ'], [], [], [], [], ['institution', 'army_unit', 'friendship', 'organization', 'visitor', 'social_gathering', 'set', 'complement', 'unit', 'consort'], [], ['committee', 'lumber', 'sheet', 'fare', 'display', 'table', 'electrical_device', 'printed_circuit', 'surface', 'enter', 'populate', 'use', 'provide'], [], ['administrator', 'committee_member', 'supervisor', 'film_maker', 'musician'], ['multitude', 'motion', 'travel', 'result', 'travel', 'obey', 'result', 'imitate', 'be', 'choose', 'imitate', 'analyze', 'check', 'play', 'originate', 'act', 'practice', 'travel', 'understand', 'persevere'], ['engineering'], ['acquiring', 'transferred_property', 'basic_cognitive_process', 'ability'], [], [], [], [], [], ['inflammation', 'originator', 'skilled_worker', 'fail', 'sink', 'change', 'stumble'], [], ['presiding_officer', 'head'], [], [], ['corporate_executive'], [], [], []]\n",
            "Hyponyms:  [[], ['abound', 'attend', 'coexist', 'equate', 'compose', 'cox', 'body', 'set_back'], [], ['kalon_tripa'], [], ['administrator', 'baas', 'indian_chief'], ['corporate_executive', 'bush_administration', 'commissioner'], ['adjutant', 'probation_officer', 'bobby', 'master'], [], [], [], [], [], ['cobalt_60'], [], ['cofounder', 'bell_founder', 'break'], [], ['cooking_apple'], [], [], ['kalon_tripa'], [], [], ['stockholder_of_record'], [], [], [], ['vitamin_a1'], ['areopagite', 'chelicera', 'cock'], [], [], [], [], ['broadcasting_company', 'trainband', 'freemasonry', 'ballet_company', 'attendance', 'fatigue_party'], [], ['advisory_board', 'chipboard', 'aquaplane', 'training_table', 'big_board', 'dining-room_table', 'dashboard', 'cpu_board', 'backgammon_board', 'catch', 'live_in'], [], ['bank_manager', 'stage_director', 'bandleader'], ['claque', 'shadowing', 'carry', 'ascend', 'conform_to', 'go_by', 'adhere', 'guard', 'accede', 'cox', 'chase'], [], ['acceptance', 'accession', 'conditioning', 'craft'], [], [], [], [], [], ['cofounder', 'bell_founder', 'break'], [], ['kalon_tripa'], [], [], [], [], [], []]\n",
            "Meronyms:  [[], ['aberdeen'], [], [], [], [], [], [], [], [], [], [], [], ['arkansas'], [], [], [], ['apple'], [], [], [], [], [], [], [], [], [], ['picometer', 'milliampere'], ['glans_penis'], [], [], [], [], [], [], ['knot', 'idiot_light'], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]\n",
            "Holonyms:  [[], ['united_states'], [], [], [], [], [], [], [], [], [], [], [], ['united_states'], [], [], [], ['apple'], [], [], [], [], ['adulthood'], [], [], [], [], ['nanometer', 'abampere'], ['male_genitalia'], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]\n",
            "\n"
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          "name": "stdout"
        }
      ]
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        "colab": {
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          "height": 358
        }
      },
      "source": [
        "sentence = \"In 2017, Amazon acquired Whole Foods Market for \\\n",
        "US$13.4 billion, which vastly increased Amazon's presence as a brickand-mortar retailer.\"\n",
        "displacy.render(nlp(sentence), style='dep', jupyter=True, options={'distance': 90})"
      ],
      "execution_count": 0,
      "outputs": [
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          "metadata": {
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    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XMnrkpqJBpNz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}