Examples with Word edu.illinois.cs.cogcomp.lbjava.nlp.Word used on opensource projects

Example 11 with Word

use of edu.illinois.cs.cogcomp.lbjava.nlp.Word in project cogcomp-nlp by CogComp.

the class ColumnFileReader method next.

public Object next() {
    String token = null;
    String pos = null;
    String label = null;
    linec++;
    // Skip to start of next line, skip unnecessary blank lines, headers and so on.
    String[] line = (String[]) super.next();
    while (line != null && (line.length == 0 || (line.length > 4 && line[4].equals("-X-")))) {
        line = (String[]) super.next();
        linec++;
    }
    if (line == null)
        return null;
    // parse the data, CoNLL 2002 or CoNLL 2003.
    if (line.length == 2) {
        token = line[0];
        label = line[1];
    } else {
        token = line[5];
        label = line[0];
        pos = line[4];
    }
    LinkedVector res = new LinkedVector();
    NEWord w = new NEWord(new Word(token, pos), null, label);
    NEWord.addTokenToSentence(res, w.form, w.neLabel);
    for (line = (String[]) super.next(); line != null && line.length > 0; line = (String[]) super.next()) {
        linec++;
        // parse the data, CoNLL 2002 or CoNLL 2003.
        if (line.length == 2) {
            token = line[0];
            label = line[1];
        } else if (line.length > 5) {
            token = line[5];
            label = line[0];
            pos = line[4];
        } else {
            System.out.println("Line " + linec + " in " + filename + " is wrong with " + line.length);
            for (String a : line) System.out.print(":" + a);
            System.out.println();
            continue;
        }
        w = new NEWord(new Word(token, pos), null, label);
        NEWord.addTokenToSentence(res, w.form, w.neLabel);
    }
    if (res.size() == 0)
        return null;
    return res;
}

Example 12 with Word

use of edu.illinois.cs.cogcomp.lbjava.nlp.Word in project cogcomp-nlp by CogComp.

the class IllinoisTokenizer method tokenizeTextSpan.

/**
     * given a span of text, return a list of {@literal Pair< String[], IntPair[] >} corresponding
     * to tokenized sentences, where the String[] is the ordered list of sentence tokens and the
     * IntPair[] is the corresponding list of character offsets with respect to <b>the original
     * text</b>.
     *
     * @param text an arbitrary span of text.
     * @return a {@link Tokenization} object containing the ordered token strings, their character
     *         offsets, and sentence end positions (as one-past-the-end token offsets)
     */
@Override
public Tokenization tokenizeTextSpan(String text) {
    String[] splitterInput = new String[1];
    splitterInput[0] = text;
    SentenceSplitter splitter = new SentenceSplitter(splitterInput);
    Sentence[] sentences = splitter.splitAll();
    List<IntPair> characterOffsets = new LinkedList<>();
    int[] sentenceEndTokenOffsets = new int[sentences.length];
    int sentenceEndTokenIndex = 0;
    int sentIndex = 0;
    List<String> tokens = new LinkedList<>();
    for (Sentence s : splitter.splitAll()) {
        LinkedVector words = s.wordSplit();
        if (s.end >= text.length()) {
            throw new IllegalArgumentException("Error in tokenizer, sentence end ( " + s.end + ") is greater than rawtext length (" + text.length() + ").");
        }
        for (int i = 0; i < words.size(); i++) {
            Word word = (Word) words.get(i);
            IntPair wordOffsets = new IntPair(word.start, word.end + 1);
            characterOffsets.add(wordOffsets);
            tokens.add(text.substring(wordOffsets.getFirst(), wordOffsets.getSecond()));
        }
        sentenceEndTokenIndex += words.size();
        sentenceEndTokenOffsets[sentIndex++] = sentenceEndTokenIndex;
    }
    String[] tokenArray = tokens.toArray(new String[tokens.size()]);
    IntPair[] charOffsetArray = characterOffsets.toArray(new IntPair[characterOffsets.size()]);
    return new Tokenization(tokenArray, charOffsetArray, sentenceEndTokenOffsets);
}

Example 13 with Word

use of edu.illinois.cs.cogcomp.lbjava.nlp.Word in project cogcomp-nlp by CogComp.

the class POSTag method main.

/**
     * Implements the program described above.
     *
     * @param args The command line parameters.
     **/
public static void main(String[] args) {
    // Parse the command line
    if (!(args.length == 1 && !args[0].startsWith("-") || args.length == 2 && (args[0].equals("-q") || args[0].equals("--quiet")) && !args[1].startsWith("-"))) {
        System.err.println("usage: java edu.illinois.cs.cogcomp.lbj.pos.POSTag [-q] <testing set>\n" + "       If -q is specified, the only output is timing and accuracy\n" + "       information.  Otherwise, the testing set is output with\n" + "       extra tags indicating whether each prediction was correct.");
        System.exit(1);
    }
    boolean quiet = args.length == 2;
    testingFile = args[args.length - 1];
    POSTagger tagger = new POSTagger();
    BufferedReader in = open();
    int correct = 0, incorrect = 0;
    for (String line = readLine(in); line != null; line = readLine(in)) {
        LinkedVector sentence = POSBracketToVector.parsePOSBracketForm(line);
        for (Word word = (Word) sentence.get(0); word != null; word = (Word) word.next) {
            String label = word.partOfSpeech;
            word.partOfSpeech = null;
            String prediction = tagger.discreteValue(word);
            if (prediction.equals(label)) {
                ++correct;
                if (!quiet)
                    System.out.print("+");
            } else {
                ++incorrect;
                if (!quiet)
                    System.out.print("-[" + label + "]");
            }
            if (!quiet)
                System.out.print(word + " ");
        }
        if (!quiet)
            System.out.print("");
    }
    System.out.println("Accuracy: " + (100 * correct / (double) (correct + incorrect)) + "%");
}

Example 14 with Word

use of edu.illinois.cs.cogcomp.lbjava.nlp.Word in project cogcomp-nlp by CogComp.

the class ChunksAndPOSTags method main.

public static void main(String[] args) {
    String filename = null;
    try {
        filename = args[0];
        if (args.length > 1)
            throw new Exception();
    } catch (Exception e) {
        System.err.println("usage: java edu.illinois.cs.cogcomp.chunker.main.ChunksAndPOSTags <input file>");
        System.exit(1);
    }
    Chunker chunker = new Chunker();
    Parser parser = new PlainToTokenParser(new WordSplitter(new SentenceSplitter(filename)));
    String previous = "";
    for (Word w = (Word) parser.next(); w != null; w = (Word) parser.next()) {
        String prediction = chunker.discreteValue(w);
        if (prediction.startsWith("B-") || prediction.startsWith("I-") && !previous.endsWith(prediction.substring(2)))
            logger.info("[" + prediction.substring(2) + " ");
        logger.info("(" + w.partOfSpeech + " " + w.form + ") ");
        if (!prediction.equals("O") && (w.next == null || chunker.discreteValue(w.next).equals("O") || chunker.discreteValue(w.next).startsWith("B-") || !chunker.discreteValue(w.next).endsWith(prediction.substring(2))))
            logger.info("] ");
        if (w.next == null)
            logger.info("\n");
        previous = prediction;
    }
}

Example 15 with Word

use of edu.illinois.cs.cogcomp.lbjava.nlp.Word in project cogcomp-nlp by CogComp.

the class SegmentTagPlain method main.

public static void main(String[] args) {
    String taggerName = null;
    String inputFile = null;
    String parserName = null;
    try {
        taggerName = args[0];
        inputFile = args[1];
        if (args.length > 2) {
            parserName = args[2];
            if (args.length > 3)
                throw new Exception();
        }
    } catch (Exception e) {
        System.err.println("usage: java edu.illinois.cs.cogcomp.lbjava.edu.illinois.cs.cogcomp.lbjava.nlp.seg.SegmentTagPlain <word classifier> " + "<input file> \\\n" + "                                         [<parser>]");
        System.exit(1);
    }
    Classifier tagger = ClassUtils.getClassifier(taggerName);
    Parser parser;
    if (parserName == null)
        parser = new PlainToTokenParser(new WordSplitter(new SentenceSplitter(inputFile)));
    else
        parser = ClassUtils.getParser(parserName, new Class[] { Parser.class }, new Parser[] { new WordSplitter(new SentenceSplitter(inputFile)) });
    String previous = "";
    for (Word w = (Word) parser.next(); w != null; w = (Word) parser.next()) {
        String prediction = tagger.discreteValue(w);
        if (prediction.startsWith("B-") || prediction.startsWith("I-") && !previous.endsWith(prediction.substring(2)))
            System.out.print("[" + prediction.substring(2) + " ");
        System.out.print(w.form + " ");
        if (!prediction.equals("O") && (w.next == null || tagger.discreteValue(w.next).equals("O") || tagger.discreteValue(w.next).startsWith("B-") || !tagger.discreteValue(w.next).endsWith(prediction.substring(2))))
            System.out.print("] ");
        if (w.next == null)
            System.out.println();
        previous = prediction;
    }
}