{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import nltk" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* download nltk data:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[nltk_data] Downloading package punkt to /Users/Carsten/nltk_data...\n", "[nltk_data] Unzipping tokenizers/punkt.zip.\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "nltk.download('punkt')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[nltk_data] Downloading package averaged_perceptron_tagger to\n", "[nltk_data] /Users/Carsten/nltk_data...\n", "[nltk_data] Unzipping taggers/averaged_perceptron_tagger.zip.\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "nltk.download('averaged_perceptron_tagger')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* simple example" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "sentence = \"This is a test sentence.\"" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['This', 'is', 'a', 'test', 'sentence', '.']" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tokens = nltk.word_tokenize(sentence)\n", "display(tokens)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('This', 'DT'),\n", " ('is', 'VBZ'),\n", " ('a', 'DT'),\n", " ('test', 'NN'),\n", " ('sentence', 'NN'),\n", " ('.', '.')]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "taggers = nltk.pos_tag(tokens)\n", "display(taggers)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 2 }