public void write(List<Instance<OUTCOME_TYPE>> instances) throws CleartkProcessingException { if (this.delegatedDataWriter == null) throw new IllegalStateException( "delegatedDataWriter must be set before calling writeSequence"); List<Object> outcomes = new ArrayList<Object>(); for (Instance<OUTCOME_TYPE> instance : instances) { List<Feature> instanceFeatures = instance.getFeatures(); for (OutcomeFeatureExtractor outcomeFeatureExtractor : outcomeFeatureExtractors) { instanceFeatures.addAll(outcomeFeatureExtractor.extractFeatures(outcomes)); } outcomes.add(instance.getOutcome()); delegatedDataWriter.write(instance); } }
@Override public void process(JCas jCas) throws AnalysisEngineProcessException { for (Time time : JCasUtil.select(jCas, Time.class)) { List<Feature> features = new ArrayList<Feature>(); for (FeatureExtractor1<Time> extractor : this.featuresExtractors) { features.addAll(extractor.extract(jCas, time)); } if (this.isTraining()) { this.dataWriter.write(new Instance<String>(time.getTimeType(), features)); } else { time.setTimeType(this.classifier.classify(features)); } } }
@Override public void process(JCas jcas) throws AnalysisEngineProcessException { LOGGER.info( "Processing ..." ); for(Markable markable : JCasUtil.select(jcas, Markable.class)){ boolean outcome; List<Feature> features = new ArrayList<>(); for(FeatureExtractor1<Markable> extractor : extractors){ features.addAll(extractor.extract(jcas, markable)); } Instance<Boolean> instance = new Instance<>(features); if(this.isTraining()){ outcome = markable.getConfidence() > 0.5; instance.setOutcome(outcome); this.dataWriter.write(instance); }else{ Map<Boolean,Double> outcomes = this.classifier.score(features); markable.setConfidence(outcomes.get(true).floatValue()); } } LOGGER.info( "Finished." ); } }
@Override public void process(JCas jcas) throws AnalysisEngineProcessException { for(Markable markable : JCasUtil.select(jcas, Markable.class)){ boolean outcome; List<Feature> features = new ArrayList<>(); for(FeatureExtractor1<Markable> extractor : extractors){ features.addAll(extractor.extract(jcas, markable)); } Instance<Boolean> instance = new Instance<>(features); if(this.isTraining()){ outcome = markable.getConfidence() > 0.5; instance.setOutcome(outcome); this.dataWriter.write(instance); }else{ Map<Boolean,Double> outcomes = this.classifier.score(features); markable.setConfidence(outcomes.get(true).floatValue()); } } } }
this.dataWriter.write(new Instance<String>(label, features)); } else { if (this.classifier.classify(features).equals("Event")) {
this.dataWriter.write(new Instance<String>(outcome, feats)); }else{ if(!prevOutcome.equals("O") && Character.isLetterOrDigit(curChar)){
this.dataWriter.write(new Instance<String>(outcome, feats)); }else{ if(!prevOutcome.equals("O") && Character.isLetterOrDigit(curChar)){
this.dataWriter.write(new Instance<String>(outcome, features));
this.dataWriter.write(new Instance<String>(outcome, features));
this.dataWriter.write(new Instance<>(category, features));
this.dataWriter.write(new Instance<>(category, features));
relation = NO_RELATION; this.dataWriter.write(new Instance<String>(relation, features));
instance.addAll(features); instance.setOutcome(attribute); this.dataWriter.write(instance);
@Override public void process(JCas jcas) throws AnalysisEngineProcessException { for (Sentence sentence : JCasUtil.select(jcas, Sentence.class)) { Instance<Boolean> instance = new Instance<Boolean>(false, this.extractor.extract( jcas, sentence)); if (this.isTraining()) { this.dataWriter.write(instance); } else { Map<Boolean, Double> scoredOutcomes = this.classifier.score(instance.getFeatures()); Double trueScore = scoredOutcomes.get(true); if (trueScore > 0.0) { SummarySentence extractedSentence = new SummarySentence( jcas, sentence.getBegin(), sentence.getEnd()); extractedSentence.setScore(trueScore); extractedSentence.addToIndexes(); } } } }
public void process(JCas jCas) throws AnalysisEngineProcessException { // use the extractor to create features for the document DocumentAnnotation doc = (DocumentAnnotation) jCas.getDocumentAnnotationFs(); List<Feature> features = this.extractor.extract(jCas, doc); // during training, get the label for this document from the CAS if (isTraining()) { UsenetDocument document = JCasUtil.selectSingle(jCas, UsenetDocument.class); this.dataWriter.write(new Instance<String>(document.getCategory(), features)); } // during classification, use the classifier's output to create a CAS annotation else { String category = this.classifier.classify(features); UsenetDocument document = new UsenetDocument(jCas, 0, jCas.getDocumentText().length()); document.setCategory(category); document.addToIndexes(); } } }
this.dataWriter.write(new Instance<>(category, features)); if(!category.equals(NO_RELATION_CATEGORY)){ singleton = false;
dataWriter.write(featureSelection.transform(instance));
dataWriter.write(featureSelection.transform(instance));
public void process(JCas jCas) throws AnalysisEngineProcessException { DocumentAnnotation doc = (DocumentAnnotation) jCas.getDocumentAnnotationFs(); Instance<String> instance = new Instance<String>(); instance.addAll(this.extractor.extract(jCas, doc)); if (isTraining()) { UsenetDocument document = JCasUtil.selectSingle(jCas, UsenetDocument.class); instance.setOutcome(document.getCategory()); this.dataWriter.write(instance); } else { // This is classification, so classify and create UsenetDocument annotation String result = this.classifier.classify(instance.getFeatures()); UsenetDocument document = new UsenetDocument(jCas, 0, jCas.getDocumentText().length()); document.setCategory(result); document.addToIndexes(); // System.out.println("classified " + ViewURIUtil.getURI(jCas) + " as " + result + "."); } }
if (tlink != null) { instance.setOutcome(tlink.getRelationType()); this.dataWriter.write(instance);