Untitled1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2008.txt    demo.ipynb  \u001b[0m\u001b[01;34mRachna_temp\u001b[0m/         Untitled1.ipynb\r\n",
      "berts.py    \u001b[01;34mfinal\u001b[0m/      README.md            Untitled.ipynb\r\n",
      "combine.py  \u001b[01;34mInferSent\u001b[0m/  \u001b[01;34mSwitchboard-Corpus\u001b[0m/  work.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "ls \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "([0.1252448582170299, 0.4807619738204116, 0.44908871313907184, 0.28945341694458787, 0.6022167660792452, 0.5808580687327627, 0.556944055042335, 0.5539377213682883, 0.5594528709296883, 0.5433541511030234, 0.5838067108992989, 0.6392720318066127, 0.6356199714298982, 0.6026093434666718, 0.44642699383246326, 0.5489111682083355, 0.5660641069849575, 0.5572573749182644, 0.56607631430146, 0.6558708130204441, 0.6658273753019774, 0.6615888574097301, 0.6720194710657761, 0.5919698517664328, 0.40245133918294484, 0.5244610489890834, 0.5470434220207827, 0.5147266930480953, 0.55923830971646, 0.5335629333643673, 0.5253269740334123, 0.4383570037596047, 0.34963168427271857, 0.2807017543859649, 0.08238525545716346, 0.05407380704358752], [0.13580261177747646, 0.35169851505883776, 0.40643470130135706, 0.44691963205430163, 0.49084275058553195, 0.5800062966181143, 0.563913281714462, 0.5567782157801039, 0.5522482478003333, 0.5622045776440036, 0.5888109646029783, 0.6195662380452699, 0.6258337822343942, 0.5615521029096777, 0.5326491685024901, 0.5204674230085854, 0.5574108833705191, 0.5631325987348939, 0.5930681674133895, 0.6292581675412938, 0.6610956819107172, 0.6664785679258278, 0.6418593934139796, 0.5554802206717179, 0.506294079979487, 0.49131860339760364, 0.5287437213526538, 0.5403361415951127, 0.5358426453763075, 0.5393760723714132, 0.4990823037191281, 0.4377718873552452, 0.3562301474727627, 0.23757289803861564, 0.13905360562890529, 0.06351095651477949], [0, 0, 0, 0.13308666456381268, 0.08916354603258236, 0.0, 0.016093014903652447, 0.023228080838010312, 0.1013435832518419, 0.06362920459039079, 0.037022817631416016, 0.006267544189124452, 0.0, 0.06428167932471651, 0.09318461373190412, 0.25137750414305127, 0.10906768455530869, 0.10334596919093397, 0.0734104005124383, 0.037220400384534, 0.005382886015110611, 0.0, 0.024619174511848252, 0.11099834725411006, 0.16018448794634077, 0.22417750272573322, 0.011592420242458878, 0.0, 0.008026923213910742, 0.0, 0.04029376865228507, 0.10160418501616797, 0.18314592489865045, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])\n"
     ]
    }
   ],
   "source": [
    "with open(\"2008.txt\") as f:\n",
    "    text = f.read()\n",
    "    yolo = text.replace(\"=\",\"\")\n",
    "    tt = nltk.tokenize.texttiling.TextTilingTokenizer(demo_mode=True)\n",
    "    print(tt.tokenize(text))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nltk.tokenize.texttiling.TextTilingTokenizer"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}