Examples of MentionContext

opennlp.tools.coref.mention.MentionContext
Data structure representation of a mention with additional contextual information. The contextual information is used in performing coreference resolution.

Examples of opennlp.tools.coref.mention.MentionContext


  protected boolean excluded(MentionContext mention, DiscourseEntity entity) {
    if (super.excluded(mention, entity)) {
      return true;
    }
    MentionContext cec = entity.getLastExtent();
    if (!canResolve(cec)) {
      return true;
    }
    if (mention.getHeadTokenTag().startsWith("NNP")) { //mention is a propernoun
      if (cec.getHeadTokenTag().startsWith("NNP")) {
        return true; // both NNP
      }
      else {
        if (entity.getNumMentions() > 1) {
          return true;
        }
        return !canResolve(cec);
      }
    }
    else if (mention.getHeadTokenTag().startsWith("PRP")){ // mention is a speech pronoun
      // cec can be either a speech pronoun or a propernoun
      if (cec.getHeadTokenTag().startsWith("NNP")) {
        //exclude antecedents not in the same sentence when they are not pronoun 
        return (mention.getSentenceNumber() - cec.getSentenceNumber() != 0);
      }
      else if (cec.getHeadTokenTag().startsWith("PRP")){
        return false;
      }
      else {
        System.err.println("Unexpected candidate exluded: "+cec.toText());
        return true;
      }
    }
    else {
      System.err.println("Unexpected mention exluded: "+mention.toText());

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Examples of opennlp.tools.coref.mention.MentionContext

   * non-referent entity. Typcically the criteria is a hueristic for a likly referent.
   * @param de The discourse entity being considered for non-reference.
   * @return True if the entity should be used as a default referent, false otherwise. 
   */
  protected boolean defaultReferent(DiscourseEntity de) {
    MentionContext ec = de.getLastExtent();
    if (ec.getNounPhraseSentenceIndex() == 0) {
      return (true);
    }
    return (false);
  }

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Examples of opennlp.tools.coref.mention.MentionContext

      boolean referentFound = false;
      boolean hasReferentialCandidate = false;
      boolean nonReferentFound = false;
      for (int ei = 0; ei < getNumEntities(dm); ei++) {
        DiscourseEntity cde = (DiscourseEntity) dm.getEntity(ei);
        MentionContext entityMention = cde.getLastExtent();
        if (outOfRange(mention, cde)) {
          if (mention.getId() != -1 && !referentFound) {
            //System.err.println("retain: Referent out of range: "+ec.toText()+" "+ec.parse.getSpan());
          }
          break;
        }
        if (excluded(mention, cde)) {
          if (showExclusions) {
            if (mention.getId() != -1 && entityMention.getId() == mention.getId()) {
              System.err.println(this +".retain: Referent excluded: (" + mention.getId() + ") " + mention.toText() + " " + mention.getIndexSpan() + " -> (" + entityMention.getId() + ") " + entityMention.toText() + " " + entityMention.getSpan() + " " + this);
            }
          }
        }
        else {
          hasReferentialCandidate = true;
          boolean useAsDifferentExample = defaultReferent(cde);
          //if (!sampleSelection || (mention.getId() != -1 && entityMention.getId() == mention.getId()) || (!nonReferentFound && useAsDifferentExample)) {
            List features = getFeatures(mention, cde);


            //add Event to Model
            if (debugOn) {
              System.err.println(this +".retain: " + mention.getId() + " " + mention.toText() + " -> " + entityMention.getId() + " " + cde);
            }
            if (mention.getId() != -1 && entityMention.getId() == mention.getId()) {
              referentFound = true;
              events.add(new Event(SAME, (String[]) features.toArray(new String[features.size()])));
              de = cde;
              //System.err.println("MaxentResolver.retain: resolved at "+ei);
              distances.add(new Integer(ei));

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Examples of opennlp.tools.coref.mention.MentionContext

  
  private String getSemanticCompatibilityFeature(MentionContext ec, DiscourseEntity de) {
    if (simModel != null) {
      double best = 0;
      for (Iterator xi = de.getMentions(); xi.hasNext();) {
        MentionContext ec2 = (MentionContext) xi.next();
        double sim = simModel.compatible(ec, ec2);
        if (debugOn) {
          System.err.println("MaxentResolver.getSemanticCompatibilityFeature: sem-compat " + sim + " " + ec.toText() + " " + ec2.toText());
        }
        if (sim > best) {
          best = sim;
        }
      }

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Examples of opennlp.tools.coref.mention.MentionContext

   * @param entity The entity.
   * @return list of distance features for the specified mention and entity.
   */
  protected List getDistanceFeatures(MentionContext mention, DiscourseEntity entity) {
    List features = new ArrayList();
    MentionContext cec = entity.getLastExtent();
    int entityDistance = mention.getNounPhraseDocumentIndex()- cec.getNounPhraseDocumentIndex();
    int sentenceDistance = mention.getSentenceNumber() - cec.getSentenceNumber();
    int hobbsEntityDistance;
    if (sentenceDistance == 0) {
      hobbsEntityDistance = cec.getNounPhraseSentenceIndex();
    }
    else {
      //hobbsEntityDistance = entityDistance - (entities within sentence from mention to end) + (entities within sentence form start to mention) 
      //hobbsEntityDistance = entityDistance - (cec.maxNounLocation - cec.getNounPhraseSentenceIndex) + cec.getNounPhraseSentenceIndex; 
      hobbsEntityDistance = entityDistance + (2 * cec.getNounPhraseSentenceIndex()) - cec.getMaxNounPhraseSentenceIndex();
    }
    features.add("hd=" + hobbsEntityDistance);
    features.add("de=" + entityDistance);
    features.add("ds=" + sentenceDistance);
    //features.add("ds=" + sdist + pronoun);

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Examples of opennlp.tools.coref.mention.MentionContext

    boolean foundIncompatiblePronoun = false;
    if (mention.getHeadTokenTag().startsWith("PRP")) {
      Map pronounMap = getPronounFeatureMap(mention.getHeadTokenText());
      //System.err.println("getPronounMatchFeatures.pronounMap:"+pronounMap);
      for (Iterator mi=entity.getMentions();mi.hasNext();) {
        MentionContext candidateMention = (MentionContext) mi.next();
        if (candidateMention.getHeadTokenTag().startsWith("PRP")) {
          if (mention.getHeadTokenText().equalsIgnoreCase(candidateMention.getHeadTokenText())) {
            foundCompatiblePronoun = true;
            break;
          }
          else {
            Map candidatePronounMap = getPronounFeatureMap(candidateMention.getHeadTokenText());
            //System.err.println("getPronounMatchFeatures.candidatePronounMap:"+candidatePronounMap);
            boolean allKeysMatch = true;
            for (Iterator ki = pronounMap.keySet().iterator(); ki.hasNext();) {
              Object key = ki.next();
              Object cfv = candidatePronounMap.get(key);

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Examples of opennlp.tools.coref.mention.MentionContext

    Parse[] mtokens = mention.getTokenParses();
    Set ecModSet = constructModifierSet(mtokens, mention.getHeadTokenIndex());
    String mentionHeadString = mention.getHeadTokenText().toLowerCase();
    Set featureSet = new HashSet();
    for (Iterator ei = entity.getMentions(); ei.hasNext();) {
      MentionContext entityMention = (MentionContext) ei.next();
      String exactMatchFeature = getExactMatchFeature(entityMention, mention);
      if (exactMatchFeature != null) {
        featureSet.add(exactMatchFeature);
      }
      else if (entityMention.getParse().isCoordinatedNounPhrase() && !mention.getParse().isCoordinatedNounPhrase()) {
        featureSet.add("cmix");
      }
      else {
        String mentionStrip = stripNp(mention);
        String entityMentionStrip = stripNp(entityMention);
        if (mentionStrip != null && entityMentionStrip != null) {
          if (isSubstring(mentionStrip, entityMentionStrip)) {
            featureSet.add("substring");
          }
        }
      }
      Parse[] xtoks = entityMention.getTokenParses();
      int headIndex = entityMention.getHeadTokenIndex();
      //if (!mention.getHeadTokenTag().equals(entityMention.getHeadTokenTag())) {
      //  //System.err.println("skipping "+mention.headTokenText+" with "+xec.headTokenText+" because "+mention.headTokenTag+" != "+xec.headTokenTag);
      //  continue;
      //}  want to match NN NNP
      String entityMentionHeadString = entityMention.getHeadTokenText().toLowerCase();
      // model lexical similarity
      if (mentionHeadString.equals(entityMentionHeadString)) {
        sameHead = true;
        featureSet.add("hds=" + mentionHeadString);
        if (!modsMatch || !nonTheModsMatch) { //only check if we haven't already found one which is the same
          modsMatch = true;
          nonTheModsMatch = true;
          Set entityMentionModifierSet = constructModifierSet(xtoks, headIndex);
          for (Iterator mi = ecModSet.iterator(); mi.hasNext();) {
            String mw = (String) mi.next();
            if (!entityMentionModifierSet.contains(mw)) {
              modsMatch = false;
              if (!mw.equals("the")) {
                nonTheModsMatch = false;
                featureSet.add("mmw=" + mw);
              }
            }
          }
        }
      }
      Set descModSet = constructModifierSet(xtoks, entityMention.getNonDescriptorStart());
      if (descModSet.contains(mentionHeadString)) {
        titleMatch = true;
      }
    }
    if (!featureSet.isEmpty()) {

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Examples of opennlp.tools.coref.mention.MentionContext

    this.parses = parses;
    parseMap = new HashMap();
    for (int ei=0,en=entities.length;ei<en;ei++) {
      if (entities[ei].getNumMentions() > 1) {
        for (Iterator mi=entities[ei].getMentions();mi.hasNext();) {
          MentionContext mc = (MentionContext) mi.next();
          Parse mentionParse = ((DefaultParse) mc.getParse()).getParse();
          parseMap.put(mentionParse,new Integer(ei+1));
          //System.err.println("CorefParse: "+mc.getParse().hashCode()+" -> "+ (ei+1));
        }
      }
    }

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Examples of opennlp.tools.coref.mention.MentionContext

   * @param mention The mention which is being considered as referential.
   * @param entity The entity to which the mention is to be resolved.
   * @return true if the entity should be excluded, false otherwise.
   */
  protected boolean excluded(MentionContext mention, DiscourseEntity entity) {
    MentionContext cec = entity.getLastExtent();
    return(mention.getSentenceNumber() == cec.getSentenceNumber() && 
     mention.getIndexSpan().getEnd() <= cec.getIndexSpan().getEnd());
  }

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Examples of opennlp.tools.coref.mention.MentionContext

    if (mention.getId() == -1) {
      return(null);
    }
    for (; ei < dm.getNumEntities(); ei++) {
      DiscourseEntity cde = dm.getEntity(ei);
      MentionContext cec = cde.getLastExtent(); // candidate extent context
      if (cec.getId() == mention.getId()) {
        distances.add(new Integer(ei));
        return (cde);
      }
    }
    //System.err.println("AbstractResolver.retain: non-refering entity with id: "+ec.toText()+" id="+ec.id);

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