package com.baeldung.apache.opennlp;

import java.io.FileInputStream;
import java.io.InputStream;
import opennlp.tools.chunker.ChunkerME;
import opennlp.tools.chunker.ChunkerModel;
import opennlp.tools.postag.POSModel;
import opennlp.tools.postag.POSTaggerME;
import opennlp.tools.tokenize.SimpleTokenizer;
import static org.assertj.core.api.Assertions.assertThat;
import org.junit.Test;

/**
 *
 * @author Parth
 */
public class ChunkerTest {

    @Test
    public void givenSentence_whenChunk_thenGetChunks() throws Exception {

        SimpleTokenizer tokenizer = SimpleTokenizer.INSTANCE;
        String[] tokens = tokenizer.tokenize("He reckons the current account deficit will narrow to only 8 billion.");

        InputStream inputStreamPOSTagger = new FileInputStream("src/main/resources/models/en-pos-maxent.bin");
        POSModel posModel = new POSModel(inputStreamPOSTagger);
        POSTaggerME posTagger = new POSTaggerME(posModel);
        String tags[] = posTagger.tag(tokens);

        InputStream inputStreamChunker = new FileInputStream("src/main/resources/models/en-chunker.bin");
        ChunkerModel chunkerModel = new ChunkerModel(inputStreamChunker);
        ChunkerME chunker = new ChunkerME(chunkerModel);
        String[] chunks = chunker.chunk(tokens, tags);
        assertThat(chunks).contains("B-NP", "B-VP", "B-NP", "I-NP", "I-NP", "I-NP", "B-VP", "I-VP", "B-PP", "B-NP", "I-NP", "I-NP", "O");
    }
}