Dependency_parsing_spaCy.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# spacy import convention\n",
    "import spacy\n",
    "\n",
    "# load the english model into nlp object.\n",
    "nlp=spacy.load('en_core_web_sm') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sample text\n",
    "text=\"Tesla founder Elon Musk has launched tech startup Neuralink.\"\n",
    "\n",
    "# returns doc container with attributes \n",
    "doc=nlp(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through doc\n",
    "# return tokens with lemmas_ (actual english language word)\n",
    "tokenized=[(token.text,token.dep_) for token in doc]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Tesla', 'compound'),\n",
       " ('founder', 'compound'),\n",
       " ('Elon', 'compound'),\n",
       " ('Musk', 'nsubj'),\n",
       " ('has', 'aux'),\n",
       " ('launched', 'ROOT'),\n",
       " ('tech', 'compound'),\n",
       " ('startup', 'compound'),\n",
       " ('Neuralink', 'dobj'),\n",
       " ('.', 'punct')]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print result.\n",
    "tokenized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'auxiliary'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# But what 'aux' means, the output of has.use spacy.explain command\n",
    "spacy.explain('aux')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- `You can find words which you don't understand using 'explain' function.`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"309.5\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"50\">Tesla</tspan>\n",
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       "\n",
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       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"225\">founder</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"225\">NOUN</tspan>\n",
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       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"400\">Elon</tspan>\n",
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       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1275\">startup</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1275\">NOUN</tspan>\n",
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       "\n",
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       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1450\">Neuralink.</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1450\">PROPN</tspan>\n",
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   ],
   "source": [
    "# Rather than see in bare text visualize it as a graph with displacy.\n",
    "from spacy import displacy\n",
    "\n",
    "doc=nlp(text)\n",
    "# specifying style is dep will render dependency_parser.\n",
    "displacy.render(doc,style='dep',manual=False) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- `It's vaild on doc or span objects only not on results like tokenized which is a list.`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# you can access head and multiple childrens.\n",
    "family_tokens=[(token.text,token.head) for token in doc]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Tesla', founder),\n",
       " ('founder', Musk),\n",
       " ('Elon', Musk),\n",
       " ('Musk', launched),\n",
       " ('has', launched),\n",
       " ('launched', launched),\n",
       " ('tech', Neuralink),\n",
       " ('startup', Neuralink),\n",
       " ('Neuralink', launched),\n",
       " ('.', launched)]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "family_tokens"
   ]
  }
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