Examples with SenseManager edu.illinois.cs.cogcomp.verbsense.core.SenseManager used on opensource projects

Example 1 with SenseManager

use of edu.illinois.cs.cogcomp.verbsense.core.SenseManager in project cogcomp-nlp by CogComp.

the class VerbSenseClassifierMain method preExtract.

@CommandDescription(description = "Pre-extracts the features for the verb-sense model. Run this before training.", usage = "preExtract")
public static void preExtract() throws Exception {
    SenseManager manager = getManager(true);
    ResourceManager conf = new VerbSenseConfigurator().getDefaultConfig();
    // If models directory doesn't exist create it
    if (!IOUtils.isDirectory(conf.getString(conf.getString(VerbSenseConfigurator.MODELS_DIRECTORY))))
        IOUtils.mkdir(conf.getString(conf.getString(VerbSenseConfigurator.MODELS_DIRECTORY)));
    int numConsumers = Runtime.getRuntime().availableProcessors();
    Dataset dataset = Dataset.PTBTrainDev;
    log.info("Pre-extracting features");
    ModelInfo modelInfo = manager.getModelInfo();
    String featureSet = "" + modelInfo.featureManifest.getIncludedFeatures().hashCode();
    String allDataCacheFile = VerbSenseConfigurator.getFeatureCacheFile(featureSet, dataset, rm);
    FeatureVectorCacheFile featureCache = preExtract(numConsumers, manager, dataset, allDataCacheFile);
    pruneFeatures(numConsumers, manager, featureCache, VerbSenseConfigurator.getPrunedFeatureCacheFile(featureSet, rm));
    Lexicon lexicon = modelInfo.getLexicon().getPrunedLexicon(manager.getPruneSize());
    log.info("Saving lexicon  with {} features to {}", lexicon.size(), manager.getLexiconFileName());
    log.info(lexicon.size() + " features in the lexicon");
    lexicon.save(manager.getLexiconFileName());
}

Example 2 with SenseManager

use of edu.illinois.cs.cogcomp.verbsense.core.SenseManager in project cogcomp-nlp by CogComp.

the class VerbSenseClassifierMain method train.

@CommandDescription(description = "Trains the verb-sense model.", usage = "train")
public static void train() throws Exception {
    SenseManager manager = getManager(true);
    int numThreads = Runtime.getRuntime().availableProcessors();
    ModelInfo modelInfo = manager.getModelInfo();
    String featureSet = "" + modelInfo.featureManifest.getIncludedFeatures().hashCode();
    String cacheFile = VerbSenseConfigurator.getPrunedFeatureCacheFile(featureSet, rm);
    AbstractInferenceSolver[] inference = new AbstractInferenceSolver[numThreads];
    // TODO Can I replace this with ILPInference?
    for (int i = 0; i < inference.length; i++) inference[i] = new MulticlassInference(manager);
    double c;
    FeatureVectorCacheFile cache;
    cache = new FeatureVectorCacheFile(cacheFile, manager);
    StructuredProblem cvProblem = cache.getStructuredProblem(20000);
    cache.close();
    LearnerParameters params = JLISLearner.crossvalStructSVMSense(cvProblem, inference, 4);
    c = params.getcStruct();
    log.info("c = {} after cv", c);
    cache = new FeatureVectorCacheFile(cacheFile, manager);
    StructuredProblem problem = cache.getStructuredProblem();
    cache.close();
    WeightVector w = JLISLearner.trainStructSVM(inference, problem, c);
    JLISLearner.saveWeightVector(w, manager.getModelFileName());
}

Example 3 with SenseManager

use of edu.illinois.cs.cogcomp.verbsense.core.SenseManager in project cogcomp-nlp by CogComp.

the class VerbSenseClassifierMain method evaluate.

@CommandDescription(description = "Performs evaluation.", usage = "evaluate")
public static void evaluate() throws Exception {
    SenseManager manager = getManager(false);
    Dataset testSet = Dataset.PTBTest;
    ILPSolverFactory solver = new ILPSolverFactory(ILPSolverFactory.SolverType.JLISCuttingPlaneGurobi);
    ClassificationTester senseTester = new ClassificationTester();
    long start = System.currentTimeMillis();
    int count = 0;
    manager.getModelInfo().loadWeightVector();
    IResetableIterator<TextAnnotation> dataset = SentenceDBHandler.instance.getDataset(testSet);
    while (dataset.hasNext()) {
        TextAnnotation ta = dataset.next();
        if (!ta.hasView(SenseManager.getGoldViewName()))
            continue;
        TokenLabelView gold = (TokenLabelView) ta.getView(SenseManager.getGoldViewName());
        ILPInference inference = manager.getInference(solver, gold.getConstituents());
        assert inference != null;
        TokenLabelView prediction = inference.getOutputView();
        evaluateSense(gold, prediction, senseTester);
        count++;
        if (count % 1000 == 0) {
            long end = System.currentTimeMillis();
            log.info(count + " sentences done. Took " + (end - start) + "ms, Micro-F1 so far = " + senseTester.getMicroF1());
        }
    }
    long end = System.currentTimeMillis();
    System.out.println(count + " sentences done. Took " + (end - start) + "ms");
    System.out.println("\n\n* Sense");
    System.out.println(senseTester.getPerformanceTable(false).toOrgTable());
}