Examples of opennlp.tools.chunker.ChunkerME.probs()

opennlp.tools.chunker.ChunkerME.probs()
Populates the specified array with the probabilities of the last decoded sequence. The sequence was determined based on the previous call to chunk. The specified array should be at least as large as the numbe of tokens in the previous call to chunk. @param probs An array used to hold the probabilities of the last decoded sequence.

                //posProbs = tagger.probs();
                if(chunker != null){
                    //we still need the Array of the best ranked POS tags for the chunker
                    String[] pos = posSequences[0].getOutcomes().toArray(new String[tokens.length]);
                    chunkSpans = chunker.chunkAsSpans(tokens, pos);
                    chunkProps = chunker.probs();
                } else if(posTypeChunker != null){
                    chunkSpans = posTypeChunker.chunkAsSpans(tokens, posTags, posProbs);
                    chunkProps = new double[chunkSpans.length];
                    Arrays.fill(chunkProps, 1.0);
                } else {

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                posList.clear(); //free memory
                
                // (2) Chunk the sentence
                
                String[] chunkTags = chunker.chunk(tokenStrings, tokenPos);
                double[] chunkProb = chunker.probs();
                if(log.isTraceEnabled()){
                    log.trace("Chunks: {}"+Arrays.toString(chunkTags));
                }
                tokenStrings = null; //free memory
                tokenPos = null; //free memory

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                posList.clear(); //free memory
                
                // (2) Chunk the sentence
                
                String[] chunkTags = chunker.chunk(tokenStrings, tokenPos);
                double[] chunkProb = chunker.probs();
                if(log.isTraceEnabled()){
                    log.trace("Chunks: {}"+Arrays.toString(chunkTags));
                }
                tokenStrings = null; //free memory
                tokenPos = null; //free memory

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                }
                Span[] chunkSpans;
                double[] chunkProps;
                if(chunker != null){
                    chunkSpans = chunker.chunkAsSpans(tokens, pos);
                    chunkProps = chunker.probs();
                } else {
                    chunkSpans = null;
                    chunkProps = null;
                }
                enhance(suggestionCache,site,ci,language, //the site, metadata and lang

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                //posProbs = tagger.probs();
                if(chunker != null){
                    //we still need the Array of the best ranked POS tags for the chunker
                    String[] pos = posSequences[0].getOutcomes().toArray(new String[tokens.length]);
                    chunkSpans = chunker.chunkAsSpans(tokens, pos);
                    chunkProps = chunker.probs();
                } else if(posTypeChunker != null){
                    chunkSpans = posTypeChunker.chunkAsSpans(tokens, posTags, posProbs);
                    chunkProps = new double[chunkSpans.length];
                    Arrays.fill(chunkProps, 1.0);
                } else {

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