Files
spring-boot-rest/libraries/src/test/java/com/baeldung/opennlp/OpenNLPTests.java
Grzegorz Piwowarek 87049b63f4 Build opt 22 06 (#2132)
* Drools reformat

* Further refactor

* Further refactor

* Refactor
2017-06-22 15:52:05 +02:00

152 lines
6.0 KiB
Java

package com.baeldung.opennlp;
import opennlp.tools.chunker.ChunkerME;
import opennlp.tools.chunker.ChunkerModel;
import opennlp.tools.cmdline.postag.POSModelLoader;
import opennlp.tools.doccat.DoccatFactory;
import opennlp.tools.doccat.DoccatModel;
import opennlp.tools.doccat.DocumentCategorizerME;
import opennlp.tools.doccat.DocumentSample;
import opennlp.tools.doccat.DocumentSampleStream;
import opennlp.tools.namefind.NameFinderME;
import opennlp.tools.namefind.TokenNameFinderModel;
import opennlp.tools.postag.POSModel;
import opennlp.tools.postag.POSSample;
import opennlp.tools.postag.POSTaggerME;
import opennlp.tools.sentdetect.SentenceDetectorME;
import opennlp.tools.sentdetect.SentenceModel;
import opennlp.tools.tokenize.WhitespaceTokenizer;
import opennlp.tools.util.InputStreamFactory;
import opennlp.tools.util.ObjectStream;
import opennlp.tools.util.PlainTextByLineStream;
import opennlp.tools.util.Span;
import opennlp.tools.util.TrainingParameters;
import org.junit.Test;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStream;
import static org.junit.Assert.assertEquals;
public class OpenNLPTests {
private final static String text = "To get to the south: Go to the store. Buy a compass. Use the compass. Then walk to the south.";
private final static String sentence[] = new String[]{"James", "Jordan", "live", "in", "Oklahoma", "city", "."};
@Test
public void givenText_WhenDetectSentences_ThenCountSentences() {
InputStream is;
SentenceModel model;
try {
is = new FileInputStream("OpenNLP/en-sent.bin");
model = new SentenceModel(is);
SentenceDetectorME sdetector = new SentenceDetectorME(model);
String sentences[] = sdetector.sentDetect(text);
assertEquals(4, sentences.length);
is.close();
} catch (IOException e) {
e.printStackTrace();
}
}
@Test
public void givenText_WhenDetectTokens_ThenVerifyNames() {
InputStream is;
TokenNameFinderModel model;
try {
is = new FileInputStream("OpenNLP/en-ner-person.bin");
model = new TokenNameFinderModel(is);
is.close();
NameFinderME nameFinder = new NameFinderME(model);
Span nameSpans[] = nameFinder.find(sentence);
String[] names = Span.spansToStrings(nameSpans, sentence);
assertEquals(1, names.length);
assertEquals("James Jordan", names[0]);
} catch (IOException e) {
e.printStackTrace();
}
}
@Test
public void givenText_WhenDetectTokens_ThenVerifyLocations() {
InputStream is;
TokenNameFinderModel model;
try {
is = new FileInputStream("OpenNLP/en-ner-location.bin");
model = new TokenNameFinderModel(is);
is.close();
NameFinderME nameFinder = new NameFinderME(model);
Span locationSpans[] = nameFinder.find(sentence);
String[] locations = Span.spansToStrings(locationSpans, sentence);
assertEquals(1, locations.length);
assertEquals("Oklahoma", locations[0]);
} catch (IOException e) {
e.printStackTrace();
}
}
@Test
public void givenText_WhenCategorizeDocument_ThenVerifyDocumentContent() {
DoccatModel docCatModel;
try {
InputStreamFactory isf = new InputStreamFactory() {
public InputStream createInputStream() throws IOException {
return new FileInputStream("OpenNLP/doc-cat.train");
}
};
ObjectStream<String> lineStream = new PlainTextByLineStream(isf, "UTF-8");
ObjectStream<DocumentSample> sampleStream = new DocumentSampleStream(lineStream);
DoccatFactory docCatFactory = new DoccatFactory();
docCatModel = DocumentCategorizerME.train("en", sampleStream, TrainingParameters.defaultParams(), docCatFactory);
DocumentCategorizerME myCategorizer = new DocumentCategorizerME(docCatModel);
double[] outcomes = myCategorizer.categorize(sentence);
String category = myCategorizer.getBestCategory(outcomes);
assertEquals("GOOD", category);
} catch (IOException e) {
e.printStackTrace();
}
}
@Test
public void givenText_WhenTagDocument_ThenVerifyTaggedString() {
try {
POSModel posModel = new POSModelLoader().load(new File("OpenNLP/en-pos-maxent.bin"));
POSTaggerME posTaggerME = new POSTaggerME(posModel);
InputStreamFactory isf = new InputStreamFactory() {
public InputStream createInputStream() throws IOException {
return new FileInputStream("OpenNLP/PartOfSpeechTag.txt");
}
};
ObjectStream<String> lineStream = new PlainTextByLineStream(isf, "UTF-8");
String line;
while ((line = lineStream.read()) != null) {
String whitespaceTokenizerLine[] = WhitespaceTokenizer.INSTANCE.tokenize(line);
String[] tags = posTaggerME.tag(whitespaceTokenizerLine);
POSSample posSample = new POSSample(whitespaceTokenizerLine, tags);
assertEquals("Out_IN of_IN the_DT night_NN that_WDT covers_VBZ me_PRP", posSample.toString());
}
lineStream.close();
} catch (IOException e) {
e.printStackTrace();
}
}
@Test
public void givenText_WhenChunked_ThenCountChunks() {
try {
InputStream is = new FileInputStream("OpenNLP/en-chunker.bin");
ChunkerModel cModel = new ChunkerModel(is);
ChunkerME chunkerME = new ChunkerME(cModel);
String pos[] = new String[]{"NNP", "NNP", "NNP", "POS", "NNP", "NN", "VBD"};
String chunks[] = chunkerME.chunk(sentence, pos);
assertEquals(7, chunks.length);
} catch (IOException e) {
e.printStackTrace();
}
}
}