Examples with SemgrexPattern edu.stanford.nlp.semgraph.semgrex.SemgrexPattern used on opensource projects

Example 1 with SemgrexPattern

use of edu.stanford.nlp.semgraph.semgrex.SemgrexPattern in project CoreNLP by stanfordnlp.

the class Mention method findDependentVerb.

private static Pair<IndexedWord, String> findDependentVerb(Mention m) {
    if (m.enhancedDependency.getRoots().size() == 0) {
        return new Pair<>();
    }
    // would be nice to condense this pattern, but sadly =reln
    // always uses the last relation in the sequence, not the first
    SemgrexPattern pattern = SemgrexPattern.compile("{idx:" + (m.headIndex + 1) + "} [ <=reln {tag:/^V.*/}=verb | <=reln ({} << {tag:/^V.*/}=verb) ]");
    SemgrexMatcher matcher = pattern.matcher(m.enhancedDependency);
    while (matcher.find()) {
        return Pair.makePair(matcher.getNode("verb"), matcher.getRelnString("reln"));
    }
    return new Pair<>();
}

Example 2 with SemgrexPattern

use of edu.stanford.nlp.semgraph.semgrex.SemgrexPattern in project CoreNLP by stanfordnlp.

the class NaturalLogicAnnotator method annotateOperators.

/**
 * Find the operators in this sentence, annotating the head word (only!) of each operator with the
 * {@link edu.stanford.nlp.naturalli.NaturalLogicAnnotations.OperatorAnnotation}.
 *
 * @param sentence As in {@link edu.stanford.nlp.naturalli.NaturalLogicAnnotator#doOneSentence(edu.stanford.nlp.pipeline.Annotation, edu.stanford.nlp.util.CoreMap)}
 */
private void annotateOperators(CoreMap sentence) {
    SemanticGraph tree = sentence.get(SemanticGraphCoreAnnotations.BasicDependenciesAnnotation.class);
    List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
    if (tree == null) {
        tree = sentence.get(SemanticGraphCoreAnnotations.EnhancedDependenciesAnnotation.class);
    }
    this.addNegationToDependencyGraph(tree);
    for (SemgrexPattern pattern : PATTERNS) {
        SemgrexMatcher matcher = pattern.matcher(tree);
        while (matcher.find()) {
            // Get terms
            IndexedWord properSubject = matcher.getNode("Subject");
            IndexedWord quantifier, subject;
            boolean namedEntityQuantifier = false;
            if (properSubject != null) {
                quantifier = subject = properSubject;
                namedEntityQuantifier = true;
            } else {
                quantifier = matcher.getNode("quantifier");
                subject = matcher.getNode("subject");
            }
            IndexedWord object = matcher.getNode("object");
            // Validate quantifier
            // At the end of this
            Optional<Triple<Operator, Integer, Integer>> quantifierInfo;
            if (namedEntityQuantifier) {
                // named entities have the "all" semantics by default.
                if (!neQuantifiers) {
                    continue;
                }
                // note: empty quantifier span given
                quantifierInfo = Optional.of(Triple.makeTriple(Operator.IMPLICIT_NAMED_ENTITY, quantifier.index(), quantifier.index()));
            } else {
                // find the quantifier, and return some info about it.
                quantifierInfo = validateQuantifierByHead(sentence, quantifier, object == null || subject == null);
            }
            // (fix up 'there are')
            if ("be".equals(subject == null ? null : subject.lemma())) {
                boolean hasExpl = false;
                IndexedWord newSubject = null;
                for (SemanticGraphEdge outgoingEdge : tree.outgoingEdgeIterable(subject)) {
                    if ("nsubj".equals(outgoingEdge.getRelation().toString())) {
                        newSubject = outgoingEdge.getDependent();
                    } else if ("expl".equals(outgoingEdge.getRelation().toString())) {
                        hasExpl = true;
                    }
                }
                if (hasExpl) {
                    subject = newSubject;
                }
            }
            // (fix up '$n$ of')
            if ("CD".equals(subject == null ? null : subject.tag())) {
                for (SemanticGraphEdge outgoingEdge : tree.outgoingEdgeIterable(subject)) {
                    String rel = outgoingEdge.getRelation().toString();
                    if (rel.startsWith("nmod") || rel.startsWith("obl")) {
                        subject = outgoingEdge.getDependent();
                    }
                }
            }
            // Set tokens
            if (quantifierInfo.isPresent()) {
                // Compute span
                IndexedWord pivot = matcher.getNode("pivot");
                if (pivot == null) {
                    pivot = object;
                }
                OperatorSpec scope = computeScope(tree, quantifierInfo.get().first, pivot, Pair.makePair(quantifierInfo.get().second, quantifierInfo.get().third), subject, namedEntityQuantifier, object, tokens.size());
                // Set annotation
                CoreLabel token = sentence.get(CoreAnnotations.TokensAnnotation.class).get(quantifier.index() - 1);
                OperatorSpec oldScope = token.get(OperatorAnnotation.class);
                if (oldScope == null || oldScope.quantifierLength() < scope.quantifierLength() || oldScope.instance != scope.instance) {
                    token.set(OperatorAnnotation.class, scope);
                } else {
                    token.set(OperatorAnnotation.class, OperatorSpec.merge(oldScope, scope));
                }
            }
        }
    }
    // Ensure we didn't select overlapping quantifiers. For example, "a" and "a few" can often overlap.
    // In these cases, take the longer quantifier match.
    List<OperatorSpec> quantifiers = new ArrayList<>();
    for (int i = 0; i < tokens.size(); ++i) {
        CoreLabel token = tokens.get(i);
        OperatorSpec operator;
        if ((operator = token.get(OperatorAnnotation.class)) != null) {
            if (i == 0 && operator.instance == Operator.NO && tokens.size() > 2 && "PRP".equals(tokens.get(1).get(CoreAnnotations.PartOfSpeechAnnotation.class))) {
                // This is pragmatically not a negation -- ignore it
                // For example, "no I don't like candy" or "no you like cats"
                token.remove(OperatorAnnotation.class);
            } else {
                quantifiers.add(operator);
            }
        }
    }
    quantifiers.sort((x, y) -> y.quantifierLength() - x.quantifierLength());
    for (OperatorSpec quantifier : quantifiers) {
        for (int i = quantifier.quantifierBegin; i < quantifier.quantifierEnd; ++i) {
            if (i != quantifier.quantifierHead) {
                tokens.get(i).remove(OperatorAnnotation.class);
            }
        }
    }
}

Example 3 with SemgrexPattern

use of edu.stanford.nlp.semgraph.semgrex.SemgrexPattern in project CoreNLP by stanfordnlp.

the class RelationTripleSegmenter method extract.

/**
 * Extract the nominal patterns from this sentence.
 *
 * @see RelationTripleSegmenter#NOUN_TOKEN_PATTERNS
 * @see RelationTripleSegmenter#NOUN_DEPENDENCY_PATTERNS
 *
 * @param parse The parse tree of the sentence to annotate.
 * @param tokens The tokens of the sentence to annotate.
 * @return A list of {@link RelationTriple}s. Note that these do not have an associated tree with them.
 */
@SuppressWarnings("unchecked")
public List<RelationTriple> extract(SemanticGraph parse, List<CoreLabel> tokens) {
    List<RelationTriple> extractions = new ArrayList<>();
    Set<Triple<Span, String, Span>> alreadyExtracted = new HashSet<>();
    // 
    for (TokenSequencePattern tokenPattern : NOUN_TOKEN_PATTERNS) {
        TokenSequenceMatcher tokenMatcher = tokenPattern.matcher(tokens);
        while (tokenMatcher.find()) {
            boolean missingPrefixBe;
            boolean missingSuffixOf = false;
            // Create subject
            List<? extends CoreMap> subject = tokenMatcher.groupNodes("$subject");
            Span subjectSpan = Util.extractNER(tokens, Span.fromValues(((CoreLabel) subject.get(0)).index() - 1, ((CoreLabel) subject.get(subject.size() - 1)).index()));
            List<CoreLabel> subjectTokens = new ArrayList<>();
            for (int i : subjectSpan) {
                subjectTokens.add(tokens.get(i));
            }
            // Create object
            List<? extends CoreMap> object = tokenMatcher.groupNodes("$object");
            Span objectSpan = Util.extractNER(tokens, Span.fromValues(((CoreLabel) object.get(0)).index() - 1, ((CoreLabel) object.get(object.size() - 1)).index()));
            if (Span.overlaps(subjectSpan, objectSpan)) {
                continue;
            }
            List<CoreLabel> objectTokens = new ArrayList<>();
            for (int i : objectSpan) {
                objectTokens.add(tokens.get(i));
            }
            // Create relation
            if (subjectTokens.size() > 0 && objectTokens.size() > 0) {
                List<CoreLabel> relationTokens = new ArrayList<>();
                // (add the 'be')
                missingPrefixBe = true;
                // (add a complement to the 'be')
                List<? extends CoreMap> beofComp = tokenMatcher.groupNodes("$beof_comp");
                if (beofComp != null) {
                    // (add the complement
                    for (CoreMap token : beofComp) {
                        if (token instanceof CoreLabel) {
                            relationTokens.add((CoreLabel) token);
                        } else {
                            relationTokens.add(new CoreLabel(token));
                        }
                    }
                    // (add the 'of')
                    missingSuffixOf = true;
                }
                // Add extraction
                String relationGloss = StringUtils.join(relationTokens.stream().map(CoreLabel::word), " ");
                if (!alreadyExtracted.contains(Triple.makeTriple(subjectSpan, relationGloss, objectSpan))) {
                    RelationTriple extraction = new RelationTriple(subjectTokens, relationTokens, objectTokens);
                    // noinspection ConstantConditions
                    extraction.isPrefixBe(missingPrefixBe);
                    extraction.isSuffixOf(missingSuffixOf);
                    extractions.add(extraction);
                    alreadyExtracted.add(Triple.makeTriple(subjectSpan, relationGloss, objectSpan));
                }
            }
        }
        // 
        for (SemgrexPattern semgrex : NOUN_DEPENDENCY_PATTERNS) {
            SemgrexMatcher matcher = semgrex.matcher(parse);
            while (matcher.find()) {
                boolean missingPrefixBe = false;
                boolean missingSuffixBe = false;
                boolean istmod = false;
                // Get relaux if applicable
                String relaux = matcher.getRelnString("relaux");
                String ignoredArc = relaux;
                if (ignoredArc == null) {
                    ignoredArc = matcher.getRelnString("arc");
                }
                // Create subject
                IndexedWord subject = matcher.getNode("subject");
                List<IndexedWord> subjectTokens = new ArrayList<>();
                Span subjectSpan;
                if (subject.ner() != null && !"O".equals(subject.ner())) {
                    subjectSpan = Util.extractNER(tokens, Span.fromValues(subject.index() - 1, subject.index()));
                    for (int i : subjectSpan) {
                        subjectTokens.add(new IndexedWord(tokens.get(i)));
                    }
                } else {
                    subjectTokens = getValidChunk(parse, subject, VALID_SUBJECT_ARCS, Optional.ofNullable(ignoredArc), true).orElse(Collections.singletonList(subject));
                    subjectSpan = Util.tokensToSpan(subjectTokens);
                }
                // Create object
                IndexedWord object = matcher.getNode("object");
                List<IndexedWord> objectTokens = new ArrayList<>();
                Span objectSpan;
                if (object.ner() != null && !"O".equals(object.ner())) {
                    objectSpan = Util.extractNER(tokens, Span.fromValues(object.index() - 1, object.index()));
                    for (int i : objectSpan) {
                        objectTokens.add(new IndexedWord(tokens.get(i)));
                    }
                } else {
                    objectTokens = getValidChunk(parse, object, VALID_OBJECT_ARCS, Optional.ofNullable(ignoredArc), true).orElse(Collections.singletonList(object));
                    objectSpan = Util.tokensToSpan(objectTokens);
                }
                // Check that the pair is valid
                if (Span.overlaps(subjectSpan, objectSpan)) {
                    // We extracted an identity
                    continue;
                }
                if (subjectSpan.end() == objectSpan.start() - 1 && (tokens.get(subjectSpan.end()).word().matches("[\\.,:;\\('\"]") || "CC".equals(tokens.get(subjectSpan.end()).tag()))) {
                    // We're straddling a clause
                    continue;
                }
                if (objectSpan.end() == subjectSpan.start() - 1 && (tokens.get(objectSpan.end()).word().matches("[\\.,:;\\('\"]") || "CC".equals(tokens.get(objectSpan.end()).tag()))) {
                    // We're straddling a clause
                    continue;
                }
                // Get any prepositional edges
                String expected = relaux == null ? "" : relaux.substring(relaux.indexOf(":") + 1).replace("_", " ");
                IndexedWord prepWord = null;
                // (these usually come from the object)
                boolean prepositionIsPrefix = false;
                for (SemanticGraphEdge edge : parse.outgoingEdgeIterable(object)) {
                    if (edge.getRelation().toString().equals("case")) {
                        prepWord = edge.getDependent();
                    }
                }
                // (...but sometimes from the subject)
                if (prepWord == null) {
                    for (SemanticGraphEdge edge : parse.outgoingEdgeIterable(subject)) {
                        if (edge.getRelation().toString().equals("case")) {
                            prepositionIsPrefix = true;
                            prepWord = edge.getDependent();
                        }
                    }
                }
                List<IndexedWord> prepChunk = Collections.EMPTY_LIST;
                if (prepWord != null && !expected.equals("tmod")) {
                    Optional<List<IndexedWord>> optionalPrepChunk = getValidChunk(parse, prepWord, Collections.singleton("mwe"), Optional.empty(), true);
                    if (!optionalPrepChunk.isPresent()) {
                        continue;
                    }
                    prepChunk = optionalPrepChunk.get();
                    Collections.sort(prepChunk, (a, b) -> {
                        double val = a.pseudoPosition() - b.pseudoPosition();
                        if (val < 0) {
                            return -1;
                        }
                        if (val > 0) {
                            return 1;
                        } else {
                            return 0;
                        }
                    });
                // ascending sort
                }
                // Get the relation
                if (subjectTokens.size() > 0 && objectTokens.size() > 0) {
                    LinkedList<IndexedWord> relationTokens = new LinkedList<>();
                    IndexedWord relNode = matcher.getNode("relation");
                    if (relNode != null) {
                        // Case: we have a grounded relation span
                        // (add the relation)
                        relationTokens.add(relNode);
                        // (add any prepositional case markings)
                        if (prepositionIsPrefix) {
                            // We're almost certainly missing a suffix 'be'
                            missingSuffixBe = true;
                            for (int i = prepChunk.size() - 1; i >= 0; --i) {
                                relationTokens.addFirst(prepChunk.get(i));
                            }
                        } else {
                            relationTokens.addAll(prepChunk);
                        }
                        if (expected.equalsIgnoreCase("tmod")) {
                            istmod = true;
                        }
                    } else {
                        // (mark it as missing a preceding 'be'
                        if (!expected.equals("poss")) {
                            missingPrefixBe = true;
                        }
                        // (add any prepositional case markings)
                        if (prepositionIsPrefix) {
                            for (int i = prepChunk.size() - 1; i >= 0; --i) {
                                relationTokens.addFirst(prepChunk.get(i));
                            }
                        } else {
                            relationTokens.addAll(prepChunk);
                        }
                        if (expected.equalsIgnoreCase("tmod")) {
                            istmod = true;
                        }
                        // (some fine-tuning)
                        if (allowNominalsWithoutNER && "of".equals(expected)) {
                            // prohibit things like "conductor of electricity" -> "conductor; be of; electricity"
                            continue;
                        }
                    }
                    // Add extraction
                    String relationGloss = StringUtils.join(relationTokens.stream().map(IndexedWord::word), " ");
                    if (!alreadyExtracted.contains(Triple.makeTriple(subjectSpan, relationGloss, objectSpan))) {
                        RelationTriple extraction = new RelationTriple(subjectTokens.stream().map(IndexedWord::backingLabel).collect(Collectors.toList()), relationTokens.stream().map(IndexedWord::backingLabel).collect(Collectors.toList()), objectTokens.stream().map(IndexedWord::backingLabel).collect(Collectors.toList()));
                        extraction.istmod(istmod);
                        extraction.isPrefixBe(missingPrefixBe);
                        extraction.isSuffixBe(missingSuffixBe);
                        extractions.add(extraction);
                        alreadyExtracted.add(Triple.makeTriple(subjectSpan, relationGloss, objectSpan));
                    }
                }
            }
        }
    }
    // 
    // Filter downward polarity extractions
    // 
    Iterator<RelationTriple> iter = extractions.iterator();
    while (iter.hasNext()) {
        RelationTriple term = iter.next();
        boolean shouldRemove = true;
        for (CoreLabel token : term) {
            if (token.get(NaturalLogicAnnotations.PolarityAnnotation.class) == null || !token.get(NaturalLogicAnnotations.PolarityAnnotation.class).isDownwards()) {
                shouldRemove = false;
            }
        }
        if (shouldRemove) {
            // Don't extract things in downward polarity contexts.
            iter.remove();
        }
    }
    // Return
    return extractions;
}

Example 4 with SemgrexPattern

use of edu.stanford.nlp.semgraph.semgrex.SemgrexPattern in project CoreNLP by stanfordnlp.

the class ApplyDepPatterns method call.

@Override
public Pair<TwoDimensionalCounter<CandidatePhrase, E>, CollectionValuedMap<E, Triple<String, Integer, Integer>>> call() throws Exception {
    // CollectionValuedMap<String, Integer> tokensMatchedPattern = new
    // CollectionValuedMap<String, Integer>();
    TwoDimensionalCounter<CandidatePhrase, E> allFreq = new TwoDimensionalCounter<>();
    CollectionValuedMap<E, Triple<String, Integer, Integer>> matchedTokensByPat = new CollectionValuedMap<>();
    for (String sentid : sentids) {
        DataInstance sent = sents.get(sentid);
        List<CoreLabel> tokens = sent.getTokens();
        for (Map.Entry<SemgrexPattern, E> pEn : patterns.entrySet()) {
            if (pEn.getKey() == null)
                throw new RuntimeException("why is the pattern " + pEn + " null?");
            SemanticGraph graph = ((DataInstanceDep) sent).getGraph();
            // SemgrexMatcher m = pEn.getKey().matcher(graph);
            // TokenSequenceMatcher m = pEn.getKey().matcher(sent);
            // //Setting this find type can save time in searching - greedy and reluctant quantifiers are not enforced
            // m.setFindType(SequenceMatcher.FindType.FIND_ALL);
            // Higher branch values makes the faster but uses more memory
            // m.setBranchLimit(5);
            Collection<ExtractedPhrase> matched = getMatchedTokensIndex(graph, pEn.getKey(), sent, label);
            for (ExtractedPhrase match : matched) {
                int s = match.startIndex;
                int e = match.endIndex + 1;
                String phrase = "";
                String phraseLemma = "";
                boolean useWordNotLabeled = false;
                boolean doNotUse = false;
                // find if the neighboring words are labeled - if so - club them together
                if (constVars.clubNeighboringLabeledWords) {
                    for (int i = s - 1; i >= 0; i--) {
                        if (tokens.get(i).get(constVars.getAnswerClass().get(label)).equals(label) && (e - i + 1) <= PatternFactory.numWordsCompoundMapped.get(label)) {
                            s = i;
                        // System.out.println("for phrase " + match + " clubbing earlier word. new s is " + s);
                        } else
                            break;
                    }
                    for (int i = e; i < tokens.size(); i++) {
                        if (tokens.get(i).get(constVars.getAnswerClass().get(label)).equals(label) && (i - s + 1) <= PatternFactory.numWordsCompoundMapped.get(label)) {
                            e = i;
                        // System.out.println("for phrase " + match + " clubbing next word. new e is " + e);
                        } else
                            break;
                    }
                }
                // to make sure we discard phrases with stopwords in between, but include the ones in which stop words were removed at the ends if removeStopWordsFromSelectedPhrases is true
                boolean[] addedindices = new boolean[e - s];
                for (int i = s; i < e; i++) {
                    CoreLabel l = tokens.get(i);
                    l.set(PatternsAnnotations.MatchedPattern.class, true);
                    if (!l.containsKey(PatternsAnnotations.MatchedPatterns.class) || l.get(PatternsAnnotations.MatchedPatterns.class) == null)
                        l.set(PatternsAnnotations.MatchedPatterns.class, new HashSet<>());
                    Pattern pSur = pEn.getValue();
                    assert pSur != null : "Why is " + pEn.getValue() + " not present in the index?!";
                    assert l.get(PatternsAnnotations.MatchedPatterns.class) != null : "How come MatchedPatterns class is null for the token. The classes in the key set are " + l.keySet();
                    l.get(PatternsAnnotations.MatchedPatterns.class).add(pSur);
                    for (Map.Entry<Class, Object> ig : constVars.getIgnoreWordswithClassesDuringSelection().get(label).entrySet()) {
                        if (l.containsKey(ig.getKey()) && l.get(ig.getKey()).equals(ig.getValue())) {
                            doNotUse = true;
                        }
                    }
                    boolean containsStop = containsStopWord(l, constVars.getCommonEngWords(), PatternFactory.ignoreWordRegex);
                    if (removePhrasesWithStopWords && containsStop) {
                        doNotUse = true;
                    } else {
                        if (!containsStop || !removeStopWordsFromSelectedPhrases) {
                            if (label == null || l.get(constVars.getAnswerClass().get(label)) == null || !l.get(constVars.getAnswerClass().get(label)).equals(label)) {
                                useWordNotLabeled = true;
                            }
                            phrase += " " + l.word();
                            phraseLemma += " " + l.lemma();
                            addedindices[i - s] = true;
                        }
                    }
                }
                for (int i = 0; i < addedindices.length; i++) {
                    if (i > 0 && i < addedindices.length - 1 && addedindices[i - 1] == true && addedindices[i] == false && addedindices[i + 1] == true) {
                        doNotUse = true;
                        break;
                    }
                }
                if (!doNotUse && useWordNotLabeled) {
                    matchedTokensByPat.add(pEn.getValue(), new Triple<>(sentid, s, e - 1));
                    if (useWordNotLabeled) {
                        phrase = phrase.trim();
                        phraseLemma = phraseLemma.trim();
                        allFreq.incrementCount(CandidatePhrase.createOrGet(phrase, phraseLemma, match.getFeatures()), pEn.getValue(), 1.0);
                    }
                }
            }
        }
    }
    return new Pair<>(allFreq, matchedTokensByPat);
}

Example 5 with SemgrexPattern

use of edu.stanford.nlp.semgraph.semgrex.SemgrexPattern in project CoreNLP by stanfordnlp.

the class ApplyDepPatterns method getMatchedTokensIndex.

private Collection<ExtractedPhrase> getMatchedTokensIndex(SemanticGraph graph, SemgrexPattern pattern, DataInstance sent, String label) {
    // TODO: look at the ignoreCommonTags flag
    ExtractPhraseFromPattern extract = new ExtractPhraseFromPattern(false, PatternFactory.numWordsCompoundMapped.get(label));
    Collection<IntPair> outputIndices = new ArrayList<>();
    boolean findSubTrees = true;
    List<CoreLabel> tokensC = sent.getTokens();
    // TODO: see if you can get rid of this (only used for matchedGraphs)
    List<String> tokens = tokensC.stream().map(x -> x.word()).collect(Collectors.toList());
    List<String> outputPhrases = new ArrayList<>();
    List<ExtractedPhrase> extractedPhrases = new ArrayList<>();
    Function<Pair<IndexedWord, SemanticGraph>, Counter<String>> extractFeatures = new Function<Pair<IndexedWord, SemanticGraph>, Counter<String>>() {

        @Override
        public Counter<String> apply(Pair<IndexedWord, SemanticGraph> indexedWordSemanticGraphPair) {
            // TODO: make features;
            Counter<String> feat = new ClassicCounter<>();
            IndexedWord vertex = indexedWordSemanticGraphPair.first();
            SemanticGraph graph = indexedWordSemanticGraphPair.second();
            List<Pair<GrammaticalRelation, IndexedWord>> pt = graph.parentPairs(vertex);
            for (Pair<GrammaticalRelation, IndexedWord> en : pt) {
                feat.incrementCount("PARENTREL-" + en.first());
            }
            return feat;
        }
    };
    extract.getSemGrexPatternNodes(graph, tokens, outputPhrases, outputIndices, pattern, findSubTrees, extractedPhrases, constVars.matchLowerCaseContext, matchingWordRestriction);
    // System.out.println("extracted phrases are " + extractedPhrases + " and output indices are " + outputIndices);
    return extractedPhrases;
}