2018-04-24 15:30:59 +02:00
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{
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"cells": [
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{
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"cell_type": "code",
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2018-04-29 18:37:21 +02:00
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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2018-04-24 15:30:59 +02:00
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"outputs": [],
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"source": [
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"import nltk"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* download nltk data:"
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]
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},
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{
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"cell_type": "code",
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2018-04-29 18:37:21 +02:00
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"execution_count": 2,
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2018-04-24 15:30:59 +02:00
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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2018-04-29 18:37:21 +02:00
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"[nltk_data] Downloading package punkt to /Users/Carsten/nltk_data...\n",
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"[nltk_data] Unzipping tokenizers/punkt.zip.\n"
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2018-04-24 15:30:59 +02:00
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]
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},
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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2018-04-29 18:37:21 +02:00
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"execution_count": 2,
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2018-04-24 15:30:59 +02:00
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"nltk.download('punkt')"
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]
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},
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{
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"cell_type": "code",
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2018-04-29 18:37:21 +02:00
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"execution_count": 3,
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2018-04-24 15:30:59 +02:00
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[nltk_data] Downloading package averaged_perceptron_tagger to\n",
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2018-04-29 18:37:21 +02:00
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"[nltk_data] /Users/Carsten/nltk_data...\n",
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"[nltk_data] Unzipping taggers/averaged_perceptron_tagger.zip.\n"
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2018-04-24 15:30:59 +02:00
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]
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},
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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2018-04-29 18:37:21 +02:00
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"execution_count": 3,
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2018-04-24 15:30:59 +02:00
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"nltk.download('averaged_perceptron_tagger')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* simple example"
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]
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},
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{
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"cell_type": "code",
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2018-04-29 18:37:21 +02:00
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"execution_count": 4,
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"metadata": {
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"collapsed": true
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},
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2018-04-24 15:30:59 +02:00
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"outputs": [],
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"source": [
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"sentence = \"This is a test sentence.\""
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]
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},
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{
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"cell_type": "code",
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2018-04-29 18:37:21 +02:00
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"execution_count": 5,
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2018-04-24 15:30:59 +02:00
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['This', 'is', 'a', 'test', 'sentence', '.']"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"tokens = nltk.word_tokenize(sentence)\n",
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"display(tokens)"
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]
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},
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{
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"cell_type": "code",
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2018-04-29 18:37:21 +02:00
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"execution_count": 6,
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2018-04-24 15:30:59 +02:00
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[('This', 'DT'),\n",
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" ('is', 'VBZ'),\n",
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" ('a', 'DT'),\n",
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" ('test', 'NN'),\n",
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" ('sentence', 'NN'),\n",
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" ('.', '.')]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"taggers = nltk.pos_tag(tokens)\n",
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"display(taggers)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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2018-04-29 18:37:21 +02:00
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"metadata": {
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"collapsed": true
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},
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2018-04-24 15:30:59 +02:00
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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