POS Tagging #2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sentence = \"People/NNS continue/VBP to/TO inquire/VB the/DT reason/?? for/IN the/DT race/NN for/IN outer/JJ space/??\"\n",
    "tokenized_sentence = sentence.split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['People/NNS',\n",
       " 'continue/VBP',\n",
       " 'to/TO',\n",
       " 'inquire/VB',\n",
       " 'the/DT',\n",
       " 'reason/??',\n",
       " 'for/IN',\n",
       " 'the/DT',\n",
       " 'race/NN',\n",
       " 'for/IN',\n",
       " 'outer/JJ',\n",
       " 'space/??']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenized_sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "str1 = 'People/NNS'\n",
    "parts = str1.split('/')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'People'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "words = [x.split('/')[0] for x in tokenized_sentence]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['People',\n",
       " 'continue',\n",
       " 'to',\n",
       " 'inquire',\n",
       " 'the',\n",
       " 'reason',\n",
       " 'for',\n",
       " 'the',\n",
       " 'race',\n",
       " 'for',\n",
       " 'outer',\n",
       " 'space']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clean_sentence = ' '.join(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'People continue to inquire the reason for the race for outer space'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import nltk\n",
    "\n",
    "tokens = nltk.word_tokenize(clean_sentence)\n",
    "posTagged = nltk.pos_tag(tokens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('People', 'NNS'),\n",
       " ('continue', 'VBP'),\n",
       " ('to', 'TO'),\n",
       " ('inquire', 'VB'),\n",
       " ('the', 'DT'),\n",
       " ('reason', 'NN'),\n",
       " ('for', 'IN'),\n",
       " ('the', 'DT'),\n",
       " ('race', 'NN'),\n",
       " ('for', 'IN'),\n",
       " ('outer', 'JJ'),\n",
       " ('space', 'NN')]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posTagged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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