Examples of edu.stanford.nlp.ling.IndexedWord

edu.stanford.nlp.ling.IndexedWord
This class is mainly for use with RTE in terms of the methods it provides, but on a more general level, it provides a {@link CoreLabel} that uses itsDocIDAnnotation, SentenceIndexAnnotation, and IndexAnnotation to implement Comparable/compareTo, hashCode, and equals. This means no other annotations, including the identity of the word, are taken into account when using these methods.
The actual implementation is to wrap a CoreLabel. This avoids breaking the equals() and hashCode() contract and also avoids expensive copying when used to represent the same data as the original CoreLabel. @author rafferty



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58   }
  
  @Override
  public void evaluate(SemanticGraph sg, SemgrexMatcher sm) {    
    String relation = sm.getRelnString(edgeName);
    IndexedWord govNode = getNamedNode(govName, sm);
    IndexedWord depNode = getNamedNode(depName, sm);
    SemanticGraphEdge edge = sg.getEdge(govNode, depNode, GrammaticalRelation.valueOf(relation));
    
    if (edge != null) {
      sg.removeEdge(edge);
    }

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43   /**
   * Used to retrieve the named node.  If not found in the SemgrexMatcher, check the
   * owning pattern object, as this could've been a created node.
   */
  public IndexedWord getNamedNode(String nodeName, SemgrexMatcher sm) {
    IndexedWord ret = sm.getNode(nodeName);
    if ((ret == null) && getOwningPattern() != null)
      return getOwningPattern().getNamedNode(nodeName);
    return ret; 
  }
 

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55 
  @Override
  public void evaluate(SemanticGraph sg, SemgrexMatcher sm) {
    boolean govWild = govName.equals(WILDCARD_NODE);
    boolean depWild = depName.equals(WILDCARD_NODE);
    IndexedWord govNode = getNamedNode(govName, sm);
    IndexedWord depNode =getNamedNode(depName, sm);


    if (govNode != null && depNode != null) {
      SemanticGraphEdge edge = sg.getEdge(govNode, depNode, relation);
      if (edge != null) {
        @SuppressWarnings("unused")

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143             // Try to get the incoming dependency edge
            int head = -1;
            String deprel = null;
            if (depTree != null) {
              Set<Integer> rootSet = depTree.getRoots().stream().map(IndexedWord::index).collect(Collectors.toSet());
              IndexedWord node = depTree.getNodeByIndexSafe(i + 1);
              if (node != null) {
                List<SemanticGraphEdge> edgeList = depTree.getIncomingEdgesSorted(node);
                if (!edgeList.isEmpty()) {
                  assert edgeList.size() == 1;
                  head = edgeList.get(0).getGovernor().index();

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78   }


  
  @Override
  public void evaluate(SemanticGraph sg, SemgrexMatcher sm) {
    IndexedWord govNode = getNamedNode(govName, sm);
    IndexedWord depNode =  getNamedNode(depName, sm);
    SemanticGraphEdge existingEdge = sg.getEdge(govNode, depNode, relation);
    if (existingEdge == null) {
      // When adding the edge, check to see if the gov/dep nodes are presently in the graph.
      // 
      if (!sg.containsVertex(govNode)) 

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43    * @param newNode String representation of new dependent IndexedFeatureNode map.
   */
  public static AddDep createEngAddDep(String govNodeName, String engRelation,  String newNode) {
    GrammaticalRelation relation = EnglishGrammaticalRelations.valueOf(engRelation);
//  IndexedWord newNodeObj = new IndexedWord(CoreLabel.fromAbstractMapLabel(IndexedFeatureLabel.valueOf(newNode, MapFactory.HASH_MAP_FACTORY)));
    IndexedWord newNodeObj = fromCheapString(newNode);
    return new AddDep(govNodeName, relation, newNodeObj);
  }
 

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94    * TODO: determine if we should be copying an IndexedWord, or working just with a FeatureLabel.
   * TODO: bombproof if this gov, dep, and reln already exist.
   */
  @Override
  public void evaluate(SemanticGraph sg, SemgrexMatcher sm) {
    IndexedWord govNode = sm.getNode(govNodeName);
    IndexedWord newNode = new IndexedWord(newNodePrototype);
    int newIndex = SemanticGraphUtils.leftMostChildVertice(govNode, sg).index(); // cheap En-specific hack for placing copula (beginning of governing phrase)
    newNode.setDocID(govNode.docID());
    newNode.setIndex(newIndex);
    newNode.setSentIndex(govNode.sentIndex());
    sg.addVertex(newNode);
    sg.addEdge(govNode, newNode, relation, weight,false);
  }
 

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161       String value = "";
      if (vals.length == 2)
        value = vals[1];
      args.put(key, value);
    }
    IndexedWord newWord = new IndexedWord();
    newWord.setWord(args.get(WORD_KEY));
    newWord.setLemma(args.get(LEMMA_KEY));
    newWord.setTag(args.get(POS_KEY));
    newWord.setValue(args.get(VALUE_KEY));
    newWord.setOriginalText(args.get(CURRENT_KEY));
    return newWord;
  }

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136       // NOTE: Semgrex can match two named nodes to the same node.  In this case, we simply,
      // check the named nodes, and if there are any collisions, we throw out this match.
      Set<String> nodeNames = matcher.getNodeNames();
      Set<IndexedWord> seen = Generics.newHashSet();
      for (String name : nodeNames) {
        IndexedWord curr = matcher.getNode(name);
        if (seen.contains(curr))
          break nextMatch;
        seen.add(curr);
//        System.out.println("REDUNDANT NODES FOUDN IN SEMGREX MATCH");
      }

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891     // GrammaticalStructure.


    List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
    List<TypedDependency> dependencies = new ArrayList<>();


    IndexedWord root = new IndexedWord(new Word("ROOT"));
    root.set(CoreAnnotations.IndexAnnotation.class, 0);


    for (int i = 1; i <= result.n; i++) {
      int head = result.getHead(i);
      String label = result.getLabel(i);


      IndexedWord thisWord = new IndexedWord(tokens.get(i - 1));
      IndexedWord headWord = head == 0 ? root
                                       : new IndexedWord(tokens.get(head - 1));


      GrammaticalRelation relation = head == 0
                                     ? GrammaticalRelation.ROOT
                                     : makeGrammaticalRelation(label);


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edu.stanford.nlp.dcoref.Document
edu.stanford.nlp.dcoref.Mention
edu.stanford.nlp.dcoref.SingletonPredictor
edu.stanford.nlp.ie.machinereading.BasicRelationFeatureFactory
edu.stanford.nlp.parser.nndep.DependencyParser
edu.stanford.nlp.pipeline.AnnotationSerializer$IntermediateSemanticGraph
edu.stanford.nlp.pipeline.CoNLLOutputter
edu.stanford.nlp.pipeline.ProtobufAnnotationSerializer
edu.stanford.nlp.semgraph.SemanticGraph
edu.stanford.nlp.semgraph.SemanticGraph$SemanticGraphParsingTask



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