@SuppressWarnings("unchecked") public Event[] updateContext(Sequence sequence, AbstractModel model) { TokenNameFinder tagger = new NameFinderME(new TokenNameFinderModel( "x-unspecified", model, Collections.emptyMap(), null)); String[] sentence = ((Sequence<NameSample>) sequence).getSource().getSentence(); String[] tags = seqCodec.encode(tagger.find(sentence), sentence.length); Event[] events = new Event[sentence.length]; NameFinderEventStream.generateEvents(sentence,tags,pcg).toArray(events); return events; }
@Override protected Iterator<Event> createEvents(NameSample sample) { if (sample.isClearAdaptiveDataSet()) { contextGenerator.clearAdaptiveData(); } Span[] names = sample.getNames(); if (!Objects.isNull(this.defaultType)) { overrideType(names); } String[] outcomes = codec.encode(names, sample.getSentence().length); // String outcomes[] = generateOutcomes(sample.getNames(), type, sample.getSentence().length); additionalContextFeatureGenerator.setCurrentContext(sample.getAdditionalContext()); String[] tokens = new String[sample.getSentence().length]; for (int i = 0; i < sample.getSentence().length; i++) { tokens[i] = sample.getSentence()[i]; } return generateEvents(tokens, outcomes, contextGenerator).iterator(); }
@SuppressWarnings("unchecked") public Event[] updateContext(Sequence sequence, AbstractModel model) { TokenNameFinder tagger = new NameFinderME(new TokenNameFinderModel( "x-unspecified", model, Collections.emptyMap(), null)); String[] sentence = ((Sequence<NameSample>) sequence).getSource().getSentence(); String[] tags = seqCodec.encode(tagger.find(sentence), sentence.length); Event[] events = new Event[sentence.length]; NameFinderEventStream.generateEvents(sentence,tags,pcg).toArray(events); return events; }
@SuppressWarnings("unchecked") public Event[] updateContext(Sequence sequence, AbstractModel model) { TokenNameFinder tagger = new NameFinderME(new TokenNameFinderModel( "x-unspecified", model, Collections.emptyMap(), null)); String[] sentence = ((Sequence<NameSample>) sequence).getSource().getSentence(); String[] tags = seqCodec.encode(tagger.find(sentence), sentence.length); Event[] events = new Event[sentence.length]; NameFinderEventStream.generateEvents(sentence,tags,pcg).toArray(events); return events; }
@Override protected Iterator<Event> createEvents(NameSample sample) { if (sample.isClearAdaptiveDataSet()) { contextGenerator.clearAdaptiveData(); } Span[] names = sample.getNames(); if (!Objects.isNull(this.defaultType)) { overrideType(names); } String[] outcomes = codec.encode(names, sample.getSentence().length); // String outcomes[] = generateOutcomes(sample.getNames(), type, sample.getSentence().length); additionalContextFeatureGenerator.setCurrentContext(sample.getAdditionalContext()); String[] tokens = new String[sample.getSentence().length]; for (int i = 0; i < sample.getSentence().length; i++) { tokens[i] = sample.getSentence()[i]; } return generateEvents(tokens, outcomes, contextGenerator).iterator(); }
@Override protected Iterator<Event> createEvents(NameSample sample) { if (sample.isClearAdaptiveDataSet()) { contextGenerator.clearAdaptiveData(); } Span[] names = sample.getNames(); if (!Objects.isNull(this.defaultType)) { overrideType(names); } String[] outcomes = codec.encode(names, sample.getSentence().length); // String outcomes[] = generateOutcomes(sample.getNames(), type, sample.getSentence().length); additionalContextFeatureGenerator.setCurrentContext(sample.getAdditionalContext()); String[] tokens = new String[sample.getSentence().length]; for (int i = 0; i < sample.getSentence().length; i++) { tokens[i] = sample.getSentence()[i]; } return generateEvents(tokens, outcomes, contextGenerator).iterator(); }