Example usage for edu.stanford.nlp.semgraph SemanticGraph hasChildWithReln

List of usage examples for edu.stanford.nlp.semgraph SemanticGraph hasChildWithReln

  1. HOME
  2. Java
  3. edu.stanford.nlp
  4. edu.stanford.nlp.semgraph.*
  5. SemanticGraph
  6. hasChildWithReln

Introduction

In this page you can find the example usage for edu.stanford.nlp.semgraph SemanticGraph hasChildWithReln.

Prototype

public boolean hasChildWithReln(IndexedWord vertex, GrammaticalRelation reln)

Source Link

Document

Does the given vertex have at least one child with the given reln ?

Usage

From source file:edu.anu.spice.SpiceParser.java

License:Open Source License

/**
 * Attaches particles to the main predicate.
 *//*ww w .  j  a v a 2s  .  co m*/
protected String getPredicate(SemanticGraph sg, IndexedWord mainPred) {
    if (sg.hasChildWithReln(mainPred, UniversalEnglishGrammaticalRelations.PHRASAL_VERB_PARTICLE)) {
        IndexedWord part = sg.getChildWithReln(mainPred,
                UniversalEnglishGrammaticalRelations.PHRASAL_VERB_PARTICLE);
        return String.format("%s %s", mainPred.lemma().equals("be") ? "" : mainPred.lemma(), part.value());
    }
    return mainPred.lemma();
}

From source file:edu.anu.spice.SpiceParser.java

License:Open Source License

/**
 * Checks if a word has a numerical modifier, and if so adds it as an object
 * with attribute//from  w  ww .ja  va  2s. co m
 */
protected void checkForNumericAttribute(ProposedTuples tuples, SemanticGraph sg, IndexedWord word) {
    if (sg.hasChildWithReln(word, UniversalEnglishGrammaticalRelations.NUMERIC_MODIFIER)) {
        IndexedWord nummod = sg.getChildWithReln(word, UniversalEnglishGrammaticalRelations.NUMERIC_MODIFIER);
        /* Prevent things like "number 5" */
        if (nummod.index() < word.index()) {
            tuples.addTuple(word, nummod);
        }
    } else if (sg.hasChildWithReln(word, SemanticGraphEnhancer.QMOD_RELATION)) {
        IndexedWord qmod = sg.getChildWithReln(word, SemanticGraphEnhancer.QMOD_RELATION);
        tuples.addTuple(word, qmod);
    }
}

From source file:edu.anu.spice.SpiceParser.java

License:Open Source License

protected ProposedTuples parseAnnotation(Annotation ann) {
    ProposedTuples tuples = new ProposedTuples();
    ArrayList<SemanticGraph> sgs = new ArrayList<SemanticGraph>();
    for (CoreMap sentence : ann.get(CoreAnnotations.SentencesAnnotation.class)) {
        SemanticGraph sg = sentence
                .get(SemanticGraphCoreAnnotations.CollapsedCCProcessedDependenciesAnnotation.class);
        sgs.add(sg);//from w w w. j  a v  a  2s .  c  o m
    }
    for (SemanticGraph sg : sgs) {
        // Everything from RuleBasedParser except resolvePlurals(sg);
        SemanticGraphEnhancer.processQuanftificationModifiers(sg);
        SemanticGraphEnhancer.collapseCompounds(sg);
        SemanticGraphEnhancer.collapseParticles(sg);
        SemanticGraphEnhancer.resolvePronouns(sg);

        SemgrexMatcher matcher = SUBJ_PRED_OBJ_TRIPLET_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord subj = matcher.getNode("subj");
            IndexedWord obj = matcher.getNode("obj");
            IndexedWord pred = matcher.getNode("pred");
            String reln = matcher.getRelnString("objreln");
            String predicate = getPredicate(sg, pred);
            if (reln.startsWith("nmod:") && !reln.equals("nmod:poss") && !reln.equals("nmod:agent")) {
                predicate += reln.replace("nmod:", " ").replace("_", " ");
            }
            tuples.addTuple(subj, obj, predicate);
        }

        matcher = ACL_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord subj = matcher.getNode("subj");
            IndexedWord obj = matcher.getNode("obj");
            IndexedWord pred = matcher.getNode("pred");
            String reln = matcher.getRelnString("objreln");
            String predicate = getPredicate(sg, pred);
            if (reln.startsWith("nmod:") && !reln.equals("nmod:poss") && !reln.equals("nmod:agent")) {
                predicate += reln.replace("nmod:", " ").replace("_", " ");
            }
            tuples.addTuple(subj, obj, predicate);
        }

        SemgrexPattern[] subjPredPatterns = { SUBJ_PRED_PAIR_PATTERN, COPULAR_PATTERN };
        for (SemgrexPattern p : subjPredPatterns) {
            matcher = p.matcher(sg);
            while (matcher.find()) {
                IndexedWord subj = matcher.getNode("subj");
                IndexedWord pred = matcher.getNode("pred");
                if (sg.hasChildWithReln(pred, UniversalEnglishGrammaticalRelations.CASE_MARKER)) {
                    IndexedWord caseMarker = sg.getChildWithReln(pred,
                            UniversalEnglishGrammaticalRelations.CASE_MARKER);
                    String prep = caseMarker.value();
                    if (sg.hasChildWithReln(caseMarker,
                            UniversalEnglishGrammaticalRelations.MULTI_WORD_EXPRESSION)) {
                        for (IndexedWord additionalCaseMarker : sg.getChildrenWithReln(caseMarker,
                                UniversalEnglishGrammaticalRelations.MULTI_WORD_EXPRESSION)) {
                            prep = prep + " " + additionalCaseMarker.value();
                        }
                    }
                    tuples.addTuple(subj, pred, prep);
                } else {
                    if (!pred.lemma().equals("be")) {
                        tuples.addTuple(subj, pred);
                    }
                }
            }
        }

        matcher = ADJ_MOD_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord obj = matcher.getNode("obj");
            IndexedWord adj = matcher.getNode("adj");
            tuples.addTuple(obj, adj);
        }

        matcher = ADJ_PRED_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord obj = matcher.getNode("obj");
            IndexedWord adj = matcher.getNode("adj");
            tuples.addTuple(obj, adj);
        }

        matcher = PP_MOD_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord gov = matcher.getNode("gov");
            IndexedWord mod = matcher.getNode("mod");
            String reln = matcher.getRelnString("reln");
            String predicate = reln.replace("nmod:", "").replace("_", " ");
            if (predicate.equals("poss") || predicate.equals("agent")) {
                continue;
            }
            tuples.addTuple(gov, mod, predicate);
        }

        matcher = POSS_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord gov = matcher.getNode("gov");
            IndexedWord mod = matcher.getNode("mod");
            tuples.addTuple(mod, gov, "have");
        }

        matcher = AGENT_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord subj = matcher.getNode("subj");
            IndexedWord obj = matcher.getNode("obj");
            IndexedWord pred = matcher.getNode("pred");
            tuples.addTuple(subj, obj, getPredicate(sg, pred));
        }

        matcher = PLURAL_SUBJECT_OBJECT_PATTERN.matcher(sg);
        while (matcher.findNextMatchingNode()) {
            IndexedWord subj = matcher.getNode("subj");
            IndexedWord obj = matcher.getNode("obj");
            checkForNumericAttribute(tuples, sg, subj);
            checkForNumericAttribute(tuples, sg, obj);
        }

        matcher = PLURAL_SUBJECT_PATTERN.matcher(sg);
        while (matcher.findNextMatchingNode()) {
            IndexedWord subj = matcher.getNode("subj");
            checkForNumericAttribute(tuples, sg, subj);
        }

        matcher = PLURAL_OTHER_PATTERN.matcher(sg);
        while (matcher.findNextMatchingNode()) {
            IndexedWord word = matcher.getNode("word");
            checkForNumericAttribute(tuples, sg, word);
        }

        matcher = COMPOUND_NOUN_PATTERN.matcher(sg);
        Set<IndexedWord> compoundNouns = new HashSet<IndexedWord>();
        while (matcher.find()) {
            IndexedWord tail = matcher.getNode("tail");
            IndexedWord head = matcher.getNode("head");
            compoundNouns.add(tail);
            compoundNouns.add(head);
            tuples.addTuple(tail, head);
        }

        // Must happen last, since it will reuse existing parts of the scene
        // graph
        matcher = NOUN_CONJ_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord tail = matcher.getNode("tail");
            IndexedWord head = matcher.getNode("head");
            int original_length = tuples.tuples.size();
            for (int i = 0; i < original_length; ++i) {
                ArrayList<String> prop = tuples.tuples.get(i);
                if (prop.size() == 3 && prop.get(0).equals(head)) {
                    tuples.addTuple(head, prop.get(1), prop.get(2));
                }
                if (prop.size() == 3 && prop.get(1).equals(tail)) {
                    tuples.addTuple(tail, prop.get(1), prop.get(2));
                }
            }
        }

        matcher = NOUN_PATTERN.matcher(sg);
        while (matcher.find()) {
            IndexedWord word = matcher.getNode("word");
            if (!compoundNouns.contains(word)) {
                tuples.addTuple(word);
            }
        }
    }
    return tuples;
}