POS_tagging_spacy.ipynb

{
 "cells": [
  {
   "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=\"Success isn't easy, and that's a good thing\"\n",
    "\n",
    "# returns doc container with attributes \n",
    "doc=nlp(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through doc and return tokens with .text\n",
    "tokenized=[(token.text,token.pos_,token.tag_) for token in doc]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- `pos_ (part-of-speech), tag_ is just acroynm of original tagname.`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Success', 'NOUN', 'NN'),\n",
       " ('is', 'AUX', 'VBZ'),\n",
       " (\"n't\", 'PART', 'RB'),\n",
       " ('easy', 'ADJ', 'JJ'),\n",
       " (',', 'PUNCT', ','),\n",
       " ('and', 'CCONJ', 'CC'),\n",
       " ('that', 'DET', 'DT'),\n",
       " (\"'s\", 'AUX', 'VBZ'),\n",
       " ('a', 'DET', 'DT'),\n",
       " ('good', 'ADJ', 'JJ'),\n",
       " ('thing', 'NOUN', 'NN')]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print result.\n",
    "tokenized"
   ]
  }
 ],
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