/** * Initializes a new Span object with an existing Span which is shifted by an * offset. * * @param span * @param offset */ public Span(Span span, int offset) { this(span.start + offset, span.end + offset, span.getType(), span.getProb()); }
private void overrideType(Span[] names) { for (int i = 0; i < names.length; i++) { Span n = names[i]; names[i] = new Span(n.getStart(), n.getEnd(), this.defaultType, n.getProb()); } }
/** * Initializes a new Span object with an existing Span which is shifted by an * offset. * * @param span * @param offset */ public Span(Span span, int offset) { this(span.start + offset, span.end + offset, span.getType(), span.getProb()); }
/** * Initializes a new Span object with an existing Span which is shifted by an * offset. * * @param span * @param offset */ public Span(Span span, int offset) { this(span.start + offset, span.end + offset, span.getType(), span.getProb()); }
/** * Converts an array of OpenNLP Spans to Idyl SDK Spans. * @param spans An array of OpenNLP Spans. * @return An array of Idyl SDK Spans. */ public static ai.idylnlp.model.nlp.Span[] toSpans(Span[] spans) { List<ai.idylnlp.model.nlp.Span> s = new LinkedList<ai.idylnlp.model.nlp.Span>(); for(opennlp.tools.util.Span span : spans) { s.add(new ai.idylnlp.model.nlp.Span(span.getStart(), span.getEnd(), span.getType(), span.getProb())); } return s.toArray(new ai.idylnlp.model.nlp.Span[s.size()]); }
private void overrideType(Span[] names) { for (int i = 0; i < names.length; i++) { Span n = names[i]; names[i] = new Span(n.getStart(), n.getEnd(), this.defaultType, n.getProb()); } }
private void overrideType(Span[] names) { for (int i = 0; i < names.length; i++) { Span n = names[i]; names[i] = new Span(n.getStart(), n.getEnd(), this.defaultType, n.getProb()); } }
tokenSpans[nameSpans[j].getEnd()-1].getEnd()); double prob = nameSpans[j].getProb();
int end = tokenAnnotations.get(prediction.getEnd() - 1).getEnd(); AnnotationFS annotation = aCas.createAnnotation(predictionType, begin, end); annotation.setDoubleValue(confidenceFeature, prediction.getProb()); annotation.setStringValue(labelFeature, label); aCas.addFsToIndexes(annotation);