deleted OpenNLP (#2223)
This commit is contained in:
Jesus Boadas
@@ -1,188 +0,0 @@
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package com.baeldung.opennlp;
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import java.io.File;
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import java.io.FileInputStream;
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import java.io.IOException;
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import java.io.InputStream;
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import java.util.Arrays;
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import java.util.logging.Logger;
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import opennlp.tools.chunker.ChunkerME;
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import opennlp.tools.chunker.ChunkerModel;
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import opennlp.tools.cmdline.postag.POSModelLoader;
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import opennlp.tools.doccat.DoccatFactory;
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import opennlp.tools.doccat.DoccatModel;
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import opennlp.tools.doccat.DocumentCategorizerME;
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import opennlp.tools.doccat.DocumentSample;
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import opennlp.tools.doccat.DocumentSampleStream;
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import opennlp.tools.namefind.NameFinderME;
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import opennlp.tools.namefind.TokenNameFinderModel;
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import opennlp.tools.postag.POSModel;
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import opennlp.tools.postag.POSSample;
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import opennlp.tools.postag.POSTaggerME;
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import opennlp.tools.sentdetect.SentenceDetectorME;
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import opennlp.tools.sentdetect.SentenceModel;
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import opennlp.tools.tokenize.Tokenizer;
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import opennlp.tools.tokenize.TokenizerME;
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import opennlp.tools.tokenize.TokenizerModel;
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import opennlp.tools.tokenize.WhitespaceTokenizer;
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import opennlp.tools.util.InputStreamFactory;
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import opennlp.tools.util.InvalidFormatException;
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import opennlp.tools.util.ObjectStream;
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import opennlp.tools.util.PlainTextByLineStream;
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import opennlp.tools.util.Span;
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import opennlp.tools.util.TrainingParameters;
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public class OpenNLP {
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private final static Logger LOGGER = Logger.getLogger(OpenNLP.class.getName());
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private final static String text = buildString();
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private final static String sentence[] = new String[] { "James", "Jordan", "live", "in", "Oklahoma", "city", "." };
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private DoccatModel docCatModel;
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public static void main(String[] args) {
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new OpenNLP();
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}
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public static String buildString(){
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StringBuilder sb = new StringBuilder();
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sb.append("To get to the south:");
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sb.append(" Go to the store.");
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sb.append(" Buy a compass.");
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sb.append(" Use the compass.");
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sb.append(" Then walk to the south.");
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return sb.toString();
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}
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public OpenNLP() {
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try {
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sentenceDetector();
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tokenizer();
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nameFinder();
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locationFinder();
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trainDocumentCategorizer();
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documentCategorizer();
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partOfSpeechTagger();
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chunker();
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} catch (InvalidFormatException e) {
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e.printStackTrace();
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} catch (IOException e) {
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e.printStackTrace();
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}
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}
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public void sentenceDetector() throws InvalidFormatException, IOException {
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InputStream is = new FileInputStream("OpenNLP/en-sent.bin");
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SentenceModel model = new SentenceModel(is);
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SentenceDetectorME sdetector = new SentenceDetectorME(model);
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String sentences[] = sdetector.sentDetect(text);
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for (String sentence : sentences) {
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LOGGER.info(sentence);
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}
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is.close();
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}
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public void tokenizer() throws InvalidFormatException, IOException {
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InputStream is = new FileInputStream("OpenNLP/en-token.bin");
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TokenizerModel model = new TokenizerModel(is);
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Tokenizer tokenizer = new TokenizerME(model);
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String tokens[] = tokenizer.tokenize(text);
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for (String token : tokens) {
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LOGGER.info(token);
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}
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is.close();
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}
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public static void nameFinder() throws IOException {
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InputStream is = new FileInputStream("OpenNLP/en-ner-person.bin");
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TokenNameFinderModel model = new TokenNameFinderModel(is);
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is.close();
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NameFinderME nameFinder = new NameFinderME(model);
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Span nameSpans[] = nameFinder.find(sentence);
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String[] names = Span.spansToStrings(nameSpans, sentence);
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Arrays.stream(names).forEach(LOGGER::info);
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for (String name : names) {
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LOGGER.info(name);
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}
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}
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public static void locationFinder() throws IOException {
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InputStream is = new FileInputStream("OpenNLP/en-ner-location.bin");
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TokenNameFinderModel model = new TokenNameFinderModel(is);
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is.close();
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NameFinderME nameFinder = new NameFinderME(model);
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Span locationSpans[] = nameFinder.find(sentence);
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String[] locations = Span.spansToStrings(locationSpans, sentence);
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Arrays.stream(locations).forEach(LOGGER::info);
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for (String location : locations) {
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LOGGER.info(location);
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}
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}
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public void trainDocumentCategorizer() {
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try {
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InputStreamFactory isf = new InputStreamFactory() {
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public InputStream createInputStream() throws IOException {
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return new FileInputStream("OpenNLP/doc-cat.train");
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}
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};
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ObjectStream<String> lineStream = new PlainTextByLineStream(isf, "UTF-8");
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ObjectStream<DocumentSample> sampleStream = new DocumentSampleStream(lineStream);
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DoccatFactory docCatFactory = new DoccatFactory();
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docCatModel = DocumentCategorizerME.train("en", sampleStream, TrainingParameters.defaultParams(), docCatFactory);
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} catch (IOException e) {
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e.printStackTrace();
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}
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}
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public void documentCategorizer() {
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DocumentCategorizerME myCategorizer = new DocumentCategorizerME(docCatModel);
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double[] outcomes = myCategorizer.categorize(sentence);
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String category = myCategorizer.getBestCategory(outcomes);
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if (category.equalsIgnoreCase("GOOD")) {
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LOGGER.info("Document is positive :) ");
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} else {
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LOGGER.info("Document is negative :( ");
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}
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}
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public static void partOfSpeechTagger() throws IOException {
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try {
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POSModel posModel = new POSModelLoader().load(new File("OpenNLP/en-pos-maxent.bin"));
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POSTaggerME posTaggerME = new POSTaggerME(posModel);
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InputStreamFactory isf = new InputStreamFactory() {
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public InputStream createInputStream() throws IOException {
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return new FileInputStream("OpenNLP/PartOfSpeechTag.txt");
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}
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};
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ObjectStream<String> lineStream = new PlainTextByLineStream(isf, "UTF-8");
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String line;
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while ((line = lineStream.read()) != null) {
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String whitespaceTokenizerLine[] = WhitespaceTokenizer.INSTANCE.tokenize(line);
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String[] tags = posTaggerME.tag(whitespaceTokenizerLine);
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POSSample posSample = new POSSample(whitespaceTokenizerLine, tags);
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LOGGER.info(posSample.toString());
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}
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lineStream.close();
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} catch (IOException e) {
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e.printStackTrace();
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}
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}
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public static void chunker() throws IOException {
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InputStream is = new FileInputStream("OpenNLP/en-chunker.bin");
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ChunkerModel cModel = new ChunkerModel(is);
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ChunkerME chunkerME = new ChunkerME(cModel);
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String[] taggedSentence = new String[] {"Out", "of", "the", "night", "that", "covers", "me"};
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String pos[] = new String[] { "IN", "IN", "DT", "NN", "WDT", "VBZ", "PRP"};
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String chunks[] = chunkerME.chunk(taggedSentence, pos);
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for (String chunk : chunks) {
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LOGGER.info(chunk);
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}
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}
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}
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