Example usage for edu.stanford.nlp.ie.machinereading.structure AnnotationUtils sentenceToString

Introduction

In this page you can find the example usage for edu.stanford.nlp.ie.machinereading.structure AnnotationUtils sentenceToString.

Prototype

public static String sentenceToString(CoreMap sent) 

Source Link

Usage

From source file:bi.meteorite.sentiment.NLPStep.java

License:Apache License

private String processString(String document) {
    // shut off the annoying intialization messages
    Properties props = new Properties();
    //specify the annotators that we want to use to annotate the text.  We need a tokenized sentence with POS tags to extract sentiment.
    //this forms our pipeline
    props.setProperty("annotators", "tokenize, ssplit, parse, sentiment");
    StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
    Annotation annotation = pipeline.process(document);
    List<Sentence> sentences = new ArrayList<Sentence>();
    /*/*  w w w .  j  av a 2s.co  m*/
     * We're going to iterate over all of the sentences and extract the sentiment.  We'll adopt a majority rule policy
     */
    for (CoreMap sentence : annotation.get(CoreAnnotations.SentencesAnnotation.class)) {
        //for each sentence, we get the sentiment that CoreNLP thinks this sentence indicates.
        Tree sentimentTree = sentence.get(SentimentCoreAnnotations.AnnotatedTree.class);
        int sentimentClassIdx = RNNCoreAnnotations.getPredictedClass(sentimentTree);
        SentimentClass sentimentClass = SentimentClass.getSpecific(sentimentClassIdx);

        /*
         * Each possible sentiment has an associated probability, so let's pull the entire
         * set of probabilities across all sentiment classes.
         */
        double[] probs = new double[SentimentClass.values().length];
        {
            SimpleMatrix mat = RNNCoreAnnotations.getPredictions(sentimentTree);
            for (int i = 0; i < SentimentClass.values().length; ++i) {
                probs[i] = mat.get(i);
            }
        }
        /*
         * Add the sentence and the associated probabilities to our list.
         */
        String sentenceStr = AnnotationUtils.sentenceToString(sentence).replace("\n", "");
        sentences.add(new Sentence(probs, sentenceStr, sentimentClass));
    }
    SentimentClass sentimentClass = null;
    if (meta.getAnalysisType().equals("Wilson Score")) {
        sentimentClass = SentimentRollup.WILSON_SCORE.apply(sentences);
    } else if (meta.getAnalysisType().equals("Simple Vote Rollup")) {
        sentimentClass = SentimentRollup.SIMPLE_VOTE.apply(sentences);
    } else if (meta.getAnalysisType().equals("Longest Sentence Wins")) {
        sentimentClass = SentimentRollup.LONGEST_SENTENCE_WINS.apply(sentences);
    } else if (meta.getAnalysisType().equals("Last Sentence Wins")) {
        sentimentClass = SentimentRollup.LAST_SENTENCE_WINS.apply(sentences);
    } else if (meta.getAnalysisType().equals("Average Probabilities Rollup")) {
        sentimentClass = SentimentRollup.AVERAGE_PROBABILITIES.apply(sentences);
    }

    if (sentimentClass != null) {
        return sentimentClass.toString();
    } else
        return null;
}

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