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Posted to commits@ctakes.apache.org by tm...@apache.org on 2016/06/16 14:51:51 UTC
svn commit: r1748736 [2/5] - in /ctakes/trunk/ctakes-coreference: ./
src/main/java/org/apache/ctakes/coreference/ae/
src/main/java/org/apache/ctakes/coreference/ae/features/
src/main/java/org/apache/ctakes/coreference/ae/features/cluster/
src/main/java...
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterCoreferenceAnnotator.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterCoreferenceAnnotator.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterCoreferenceAnnotator.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterCoreferenceAnnotator.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,525 @@
+package org.apache.ctakes.coreference.ae;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.LinkedHashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Random;
+
+import org.apache.ctakes.core.util.ListFactory;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterAgreementFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterAttributeFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterDepHeadExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterSalienceFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterSectionFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterSemTypeDepPrefsFeatureExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterStackFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterStringFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterUMLSFeatureExtractor;
+import org.apache.ctakes.coreference.ae.pairing.cluster.ClusterMentionPairer_ImplBase;
+import org.apache.ctakes.coreference.ae.pairing.cluster.ClusterPairer;
+import org.apache.ctakes.coreference.ae.pairing.cluster.HeadwordPairer;
+import org.apache.ctakes.coreference.ae.pairing.cluster.SectionHeaderPairer;
+import org.apache.ctakes.coreference.ae.pairing.cluster.SentenceDistancePairer;
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.relationextractor.eval.RelationExtractorEvaluation.HashableArguments;
+import org.apache.ctakes.typesystem.type.relation.CollectionTextRelation;
+import org.apache.ctakes.typesystem.type.relation.CollectionTextRelationIdentifiedAnnotationRelation;
+import org.apache.ctakes.typesystem.type.relation.CoreferenceRelation;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.ctakes.typesystem.type.textsem.Markable;
+import org.apache.ctakes.typesystem.type.textspan.Segment;
+import org.apache.uima.UimaContext;
+import org.apache.uima.analysis_engine.AnalysisEngineDescription;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.descriptor.ConfigurationParameter;
+import org.apache.uima.fit.factory.AnalysisEngineFactory;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.apache.uima.jcas.cas.EmptyFSList;
+import org.apache.uima.jcas.cas.NonEmptyFSList;
+import org.apache.uima.resource.ResourceInitializationException;
+import org.cleartk.ml.CleartkAnnotator;
+import org.cleartk.ml.CleartkProcessingException;
+import org.cleartk.ml.DataWriter;
+import org.cleartk.ml.Feature;
+import org.cleartk.ml.Instance;
+import org.cleartk.ml.feature.extractor.FeatureExtractor1;
+import org.cleartk.ml.jar.DefaultDataWriterFactory;
+import org.cleartk.ml.jar.DirectoryDataWriterFactory;
+import org.cleartk.ml.jar.GenericJarClassifierFactory;
+import org.cleartk.util.ViewUriUtil;
+
+public class MentionClusterCoreferenceAnnotator extends CleartkAnnotator<String> {
+ public static final String NO_RELATION_CATEGORY = "-NONE-";
+ public static final String PARAM_PROBABILITY_OF_KEEPING_A_NEGATIVE_EXAMPLE =
+ "ProbabilityOfKeepingANegativeExample";
+ @ConfigurationParameter(
+ name = PARAM_PROBABILITY_OF_KEEPING_A_NEGATIVE_EXAMPLE,
+ mandatory = false,
+ description = "probability that a negative example should be retained for training")
+ protected double probabilityOfKeepingANegativeExample = 0.5;
+
+ public static final String PARAM_USE_EXISTING_ENCODERS="UseExistingEncoders";
+ @ConfigurationParameter(name = PARAM_USE_EXISTING_ENCODERS,
+ mandatory=false,
+ description = "Whether to use encoders in output directory during data writing; if we are making multiple calls")
+ private boolean useExistingEncoders=false;
+
+ protected Random coin = new Random(0);
+
+ boolean greedyFirst = true;
+
+ private static DataWriter<String> classDataWriter = null;
+
+ public static AnalysisEngineDescription createDataWriterDescription(
+ Class<? extends DataWriter<String>> dataWriterClass,
+ File outputDirectory,
+ float downsamplingRate) throws ResourceInitializationException {
+ return AnalysisEngineFactory.createEngineDescription(
+ MentionClusterCoreferenceAnnotator.class,
+ CleartkAnnotator.PARAM_IS_TRAINING,
+ true,
+ MentionClusterCoreferenceAnnotator.PARAM_PROBABILITY_OF_KEEPING_A_NEGATIVE_EXAMPLE,
+ downsamplingRate,
+ DefaultDataWriterFactory.PARAM_DATA_WRITER_CLASS_NAME,
+ dataWriterClass,
+ DirectoryDataWriterFactory.PARAM_OUTPUT_DIRECTORY,
+ outputDirectory);
+ }
+
+ public static AnalysisEngineDescription createAnnotatorDescription(
+ String modelPath) throws ResourceInitializationException {
+ return AnalysisEngineFactory.createEngineDescription(
+ MentionClusterCoreferenceAnnotator.class,
+ CleartkAnnotator.PARAM_IS_TRAINING,
+ false,
+ GenericJarClassifierFactory.PARAM_CLASSIFIER_JAR_PATH,
+ modelPath);
+ }
+
+ private List<RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation>> relationExtractors = this.getFeatureExtractors();
+ private List<FeatureExtractor1<Markable>> mentionExtractors = this.getMentionExtractors();
+ private List<ClusterMentionPairer_ImplBase> pairExtractors = this.getPairExtractors();
+
+// private Set<String> markableStrings = null;
+
+ protected List<RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation>> getFeatureExtractors() {
+ List<RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation>> extractors = new ArrayList<>();
+ extractors.add(new MentionClusterAgreementFeaturesExtractor());
+ extractors.add(new MentionClusterStringFeaturesExtractor());
+ extractors.add(new MentionClusterSectionFeaturesExtractor());
+ extractors.add(new MentionClusterUMLSFeatureExtractor());
+ extractors.add(new MentionClusterDepHeadExtractor());
+ extractors.add(new MentionClusterStackFeaturesExtractor());
+ extractors.add(new MentionClusterSalienceFeaturesExtractor());
+ extractors.add(new MentionClusterAttributeFeaturesExtractor());
+// extractors.add(new MentionClusterAttributeVectorExtractor()); // does nothing yet
+
+// extractors.add(new MentionClusterDistanceFeaturesExtractor());
+
+ try {
+// extractors.add(new MentionClusterDistSemExtractor("org/apache/ctakes/coreference/distsem/mimic_vectors.txt"));
+// extractors.add(new MentionClusterDistSemExtractor("org/apache/ctakes/coreference/distsem/deps.words"));
+ extractors.add(new MentionClusterSemTypeDepPrefsFeatureExtractor());
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+
+ return extractors;
+ }
+
+ protected List<FeatureExtractor1<Markable>> getMentionExtractors(){
+ List<FeatureExtractor1<Markable>> extractors = new ArrayList<>();
+ // mention features from pairwise system:
+ extractors.add(new MentionClusterAgreementFeaturesExtractor());
+ extractors.add(new MentionClusterSectionFeaturesExtractor());
+ extractors.add(new MentionClusterUMLSFeatureExtractor());
+ extractors.add(new MentionClusterDepHeadExtractor());
+ extractors.add(new MentionClusterSalienceFeaturesExtractor());
+
+// try{
+// extractors.add(new MentionClusterMentionFeaturesExtractor("org/apache/ctakes/coreference/distsem/ties1mil.lowercase.txt"));
+// }catch(CleartkExtractorException e){
+// e.printStackTrace();
+// }
+ extractors.add(new MentionClusterAttributeFeaturesExtractor());
+
+ return extractors;
+ }
+
+ protected List<ClusterMentionPairer_ImplBase> getPairExtractors(){
+ List<ClusterMentionPairer_ImplBase> pairers = new ArrayList<>();
+ int sentDist = 5;
+ pairers.add(new SentenceDistancePairer(sentDist));
+ pairers.add(new SectionHeaderPairer(sentDist));
+ pairers.add(new ClusterPairer(Integer.MAX_VALUE));
+ pairers.add(new HeadwordPairer());
+ return pairers;
+ }
+
+ protected Iterable<CollectionTextRelationIdentifiedAnnotationPair> getCandidateRelationArgumentPairs(
+ JCas jcas,
+ Markable mention){
+ LinkedHashSet<CollectionTextRelationIdentifiedAnnotationPair> pairs = new LinkedHashSet<>();
+ for(ClusterMentionPairer_ImplBase pairer : this.pairExtractors){
+ pairs.addAll(pairer.getPairs(jcas, mention));
+ }
+
+ return pairs;
+ }
+
+ private void resetPairers(JCas jcas){
+ for(ClusterMentionPairer_ImplBase pairer : this.pairExtractors){
+ pairer.reset(jcas);
+ }
+ }
+
+ @Override
+ public void initialize(UimaContext context) throws ResourceInitializationException {
+ super.initialize(context);
+
+ if(this.useExistingEncoders && classDataWriter != null){
+ this.dataWriter = classDataWriter;
+ }else if(this.isTraining()){
+ classDataWriter = this.dataWriter;
+ }
+ }
+
+ @Override
+ public void process(JCas jCas) throws AnalysisEngineProcessException {
+ // lookup from pair of annotations to binary text relation
+ // note: assumes that there will be at most one relation per pair
+ this.resetPairers(jCas);
+
+ Map<CollectionTextRelationIdentifiedAnnotationPair, CollectionTextRelationIdentifiedAnnotationRelation> relationLookup;
+ relationLookup = new HashMap<>();
+ if (this.isTraining()) {
+ for (CollectionTextRelation cluster : JCasUtil.select(jCas, CollectionTextRelation.class)) {
+ for(IdentifiedAnnotation mention : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ CollectionTextRelationIdentifiedAnnotationRelation relation =
+ new CollectionTextRelationIdentifiedAnnotationRelation(jCas);
+ relation.setCluster(cluster);
+ relation.setMention(mention);
+ relation.setCategory("CoreferenceClusterMember");
+ relation.addToIndexes();
+ // The key is a list of args so we can do bi-directional lookup
+ CollectionTextRelationIdentifiedAnnotationPair key = new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention);
+ if(relationLookup.containsKey(key)){
+ String cat = relationLookup.get(key).getCategory();
+ System.err.println("Error in: "+ ViewUriUtil.getURI(jCas).toString());
+ System.err.println("Error! This attempted relation " + relation.getCategory() + " already has a relation " + cat + " at this span: " + mention.getCoveredText());
+ }
+ relationLookup.put(key, relation);
+ }
+ }
+ }
+
+
+ for(Segment segment : JCasUtil.select(jCas, Segment.class)){
+ for(Markable mention : JCasUtil.selectCovered(jCas, Markable.class, segment)){
+// ConllDependencyNode headNode = DependencyUtility.getNominalHeadNode(jCas, mention);
+ boolean singleton = true;
+ double maxScore = 0.0;
+ CollectionTextRelation maxCluster = null;
+
+ for(CollectionTextRelationIdentifiedAnnotationPair pair : this.getCandidateRelationArgumentPairs(jCas, mention)){
+ CollectionTextRelation cluster = pair.getCluster();
+ // apply all the feature extractors to extract the list of features
+ List<Feature> features = new ArrayList<>();
+ for (RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation> extractor : this.relationExtractors) {
+ List<Feature> feats = extractor.extract(jCas, cluster, mention);
+ if (feats != null){
+// Logger.getRootLogger().info(String.format("For cluster with %d mentions, %d %s features", JCasUtil.select(cluster.getMembers(), Markable.class).size(), feats.size(), extractor.getClass().getSimpleName()));
+ features.addAll(feats);
+ }
+ }
+
+ for(FeatureExtractor1<Markable> extractor : this.mentionExtractors){
+ features.addAll(extractor.extract(jCas, mention));
+ }
+
+ // here is where feature conjunctions can go (dupFeatures)
+ List<Feature> dupFeatures = new ArrayList<>();
+ // sanity check on feature values
+ for (Feature feature : features) {
+ if (feature.getValue() == null) {
+ feature.setValue("NULL");
+ String message = String.format("Null value found in %s from %s", feature, features);
+ System.err.println(message);
+ // throw new IllegalArgumentException(String.format(message, feature, features));
+ }else{
+// String prefix = null;
+ // Durret and Klein style feature conjunctions: pronoun type or pos tag. maybe try umls semantic-type?
+ /*
+ if(mentionText.equals("it") || mentionText.equals("this") || mentionText.equals("that")){
+ prefix = "PRO_"+mentionText;
+ }else if(headNode != null && headNode.getPostag() != null){
+ prefix = headNode.getPostag();
+ }else{
+ prefix = "UNK";
+ }
+ */
+ // headword-based feature conjunctions
+/* if(headNode != null && headNode.getCoveredText() != null && headMatches(headNode.getCoveredText().toLowerCase(), features)){
+ prefix = "HEAD_MATCH";
+ }else{
+ prefix = "NO_HEAD_MATCH";
+ }
+*/
+
+ // UMLS semantic type feature conjunctions
+ /*
+ for(Feature feat : features){
+ if(feat.getName().startsWith("ClusterSemType")){
+ dupFeatures.add(new Feature(feat.getName()+"_"+feature.getName(), feature.getValue()));
+ }
+ }
+ */
+
+// if(prefix != null){
+// dupFeatures.add(new Feature(prefix+"_"+feature.getName(), feature.getValue()));
+// }
+ }
+ }
+
+ features.addAll(dupFeatures);
+
+ // during training, feed the features to the data writer
+ if (this.isTraining()) {
+ String category = this.getRelationCategory(relationLookup, cluster, mention);
+ if (category == null) {
+ continue;
+ }
+
+ // create a classification instance and write it to the training data
+ this.dataWriter.write(new Instance<>(category, features));
+ if(!category.equals(NO_RELATION_CATEGORY)){
+ singleton = false;
+ break;
+ }
+ }
+
+ // during classification feed the features to the classifier and create
+ // annotations
+ else {
+ String predictedCategory = this.classify(features);
+ // TODO look at scores in classifier and try best-pair rather than first-pair?
+ Map<String,Double> scores = this.classifier.score(features);
+
+ // add a relation annotation if a true relation was predicted
+ if (!predictedCategory.equals(NO_RELATION_CATEGORY)) {
+// Logger.getLogger("MCAnnotator").info(String.format("Making a pair with score %f", scores.get(predictedCategory)));
+ if(greedyFirst){
+ createRelation(jCas, cluster, mention, predictedCategory, scores.get(predictedCategory));
+ singleton = false;
+ // break here for "closest-first" greedy decoding strategy (Soon et al., 2001), terminology from Lasalle and Denis (2013),
+ // for "best first" need to keep track of all relations with scores and only keep the highest
+ break;
+ }
+ if(scores.get(predictedCategory) > maxScore){
+ maxScore = scores.get(predictedCategory);
+ maxCluster = cluster;
+ }
+ }
+ }
+ }
+ if(!this.isTraining() && !greedyFirst && maxCluster != null){
+ // make a link with the max cluster
+ createRelation(jCas, maxCluster, mention, "CoreferenceClusterMember", maxScore);
+ }
+
+ // if we got this far and never matched up the markable then add it to list.
+ // do this even during training -- adds non-chain markables to antecedent list which will be seen during testing.
+ if(singleton){
+ // make the markable it's own cluster:
+ CollectionTextRelation chain = new CollectionTextRelation(jCas);
+ NonEmptyFSList list = new NonEmptyFSList(jCas);
+ list.setHead(mention);
+ list.setTail(new EmptyFSList(jCas));
+ chain.setMembers(list);
+ chain.addToIndexes();
+ list.addToIndexes();
+ list.getTail().addToIndexes();
+ }
+ }
+ }
+
+ removeSingletonClusters(jCas);
+ }
+
+
+ /**
+ * Looks up the arguments in the specified lookup table and converts the
+ * relation into a label for classification
+ *
+ * @return If this category should not be processed for training return
+ * <i>null</i> otherwise it returns the label sent to the datawriter
+ */
+ protected String getRelationCategory(
+ Map<CollectionTextRelationIdentifiedAnnotationPair, CollectionTextRelationIdentifiedAnnotationRelation> relationLookup,
+ CollectionTextRelation cluster,
+ IdentifiedAnnotation mention) {
+ CollectionTextRelationIdentifiedAnnotationRelation relation =
+ relationLookup.get(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ String category;
+ if (relation != null) {
+ category = relation.getCategory();
+ } else if (coin.nextDouble() <= this.probabilityOfKeepingANegativeExample) {
+ category = NO_RELATION_CATEGORY;
+ } else {
+ category = null;
+ }
+ return category;
+ }
+
+ /**
+ * Predict an outcome given a set of features. By default, this simply
+ * delegates to the object's <code>classifier</code>. Subclasses may override
+ * this method to implement more complex classification procedures.
+ *
+ * @param features
+ * The features to be classified.
+ * @return The predicted outcome (label) for the features.
+ */
+ protected String classify(List<Feature> features) throws CleartkProcessingException {
+ return this.classifier.classify(features);
+ }
+
+ /**
+ * Create a UIMA relation type based on arguments and the relation label. This
+ * allows subclasses to create/define their own types: e.g. coreference can
+ * create CoreferenceRelation instead of BinaryTextRelation
+ *
+ * @param jCas
+ * - JCas object, needed to create new UIMA types
+ * @param arg1
+ * - First argument to relation
+ * @param arg2
+ * - Second argument to relation
+ * @param predictedCategory
+ * - Name of relation
+ */
+ protected void createRelation(
+ JCas jCas,
+ CollectionTextRelation cluster,
+ IdentifiedAnnotation mention,
+ String predictedCategory,
+ Double confidence) {
+ // add the relation to the CAS
+ CollectionTextRelationIdentifiedAnnotationRelation relation = new CollectionTextRelationIdentifiedAnnotationRelation(jCas);
+ relation.setCluster(cluster);
+ relation.setMention(mention);
+ relation.setCategory(predictedCategory);
+ relation.setConfidence(confidence);
+ relation.addToIndexes();
+
+// RelationArgument arg = new RelationArgument(jCas);
+// arg.setArgument(mention);
+ ListFactory.append(jCas, cluster.getMembers(), mention);
+ }
+
+
+ private static void removeSingletonClusters(JCas jcas){
+ List<CollectionTextRelation> toRemove = new ArrayList<>();
+ for(CollectionTextRelation rel : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ NonEmptyFSList head = (NonEmptyFSList) rel.getMembers();
+ if(head.getTail() instanceof EmptyFSList){
+ toRemove.add(rel);
+ }
+ }
+
+ for(CollectionTextRelation rel : toRemove){
+ rel.removeFromIndexes();
+ }
+ }
+
+// private static final boolean dominates(Annotation arg1, Annotation arg2) {
+// return (arg1.getBegin() <= arg2.getBegin() && arg1.getEnd() >= arg2.getEnd());
+// }
+
+ /*
+ public Set<String> getBestEnt(JCas jcas, CollectionTextRelation cluster){
+ Set<String> semTypes = new HashSet<>();
+ for(Markable member : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ semTypes.addAll(getBestEnt(jcas, member));
+ }
+ return semTypes;
+ }
+
+ public Set<String> getBestEnt(JCas jcas, Markable markable){
+ Set<String> bestEnts = new HashSet<>();
+ IdentifiedAnnotation bestEnt = null;
+ Set<IdentifiedAnnotation> otherBestEnts = new HashSet<>();
+ ConllDependencyNode head = DependencyUtility.getNominalHeadNode(jcas, markable);
+ Collection<IdentifiedAnnotation> coveringEnts = nodeEntMap.get(head);
+ for(IdentifiedAnnotation ent : coveringEnts){
+ if(ent.getOntologyConceptArr() == null) continue; // skip non-umls entities.
+ ConllDependencyNode entHead = DependencyUtility.getNominalHeadNode(jcas, ent);
+ if(entHead == head){
+ if(bestEnt == null){
+ bestEnt = ent;
+ }else if((ent.getEnd()-ent.getBegin()) > (bestEnt.getEnd() - bestEnt.getBegin())){
+ // if the span of this entity is bigger than the biggest existing one:
+ bestEnt = ent;
+ otherBestEnts = new HashSet<>();
+ }else if((ent.getEnd()-ent.getBegin()) == (bestEnt.getEnd() - bestEnt.getBegin())){
+ // there is another one with the exact same span and possibly different type!
+ otherBestEnts.add(ent);
+ }
+ }
+ }
+
+ if(bestEnt!=null){
+ bestEnts.add(bestEnt.getClass().getSimpleName());
+ for(IdentifiedAnnotation other : otherBestEnts){
+ bestEnts.add(other.getClass().getSimpleName());
+ }
+ }
+ return bestEnts;
+ }
+ */
+
+ public Map<HashableArguments, Double> getMarkablePairScores(JCas jCas){
+ Map<HashableArguments, Double> scoreMap = new HashMap<>();
+ for(CoreferenceRelation reln : JCasUtil.select(jCas, CoreferenceRelation.class)){
+ HashableArguments pair = new HashableArguments(reln.getArg1().getArgument(), reln.getArg2().getArgument());
+ scoreMap.put(pair, reln.getConfidence());
+ }
+ return scoreMap;
+ }
+
+ public static class CollectionTextRelationIdentifiedAnnotationPair {
+ private final CollectionTextRelation cluster;
+ private final IdentifiedAnnotation mention;
+
+ public CollectionTextRelationIdentifiedAnnotationPair(CollectionTextRelation cluster, IdentifiedAnnotation mention){
+ this.cluster = cluster;
+ this.mention = mention;
+ }
+
+ public final CollectionTextRelation getCluster(){
+ return this.cluster;
+ }
+
+ public final IdentifiedAnnotation getMention(){
+ return this.mention;
+ }
+
+ @Override
+ public boolean equals(Object obj) {
+ CollectionTextRelationIdentifiedAnnotationPair other = (CollectionTextRelationIdentifiedAnnotationPair) obj;
+ return (this.cluster == other.cluster &&
+ this.mention == other.mention);
+ }
+
+ @Override
+ public int hashCode() {
+ return 31*cluster.hashCode() + (mention==null ? 0 : mention.hashCode());
+ }
+ }
+
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterRankingCoreferenceAnnotator.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterRankingCoreferenceAnnotator.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterRankingCoreferenceAnnotator.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/MentionClusterRankingCoreferenceAnnotator.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,688 @@
+package org.apache.ctakes.coreference.ae;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.LinkedHashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Random;
+import java.util.Set;
+
+import org.apache.ctakes.core.util.ListFactory;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterAgreementFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterAttributeFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterDepHeadExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterDistSemExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterMentionFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterSalienceFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterSectionFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterSemTypeDepPrefsFeatureExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterStackFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterStringFeaturesExtractor;
+import org.apache.ctakes.coreference.ae.features.cluster.MentionClusterUMLSFeatureExtractor;
+import org.apache.ctakes.coreference.util.ClusterUtils;
+import org.apache.ctakes.dependency.parser.util.DependencyUtility;
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.relationextractor.eval.RelationExtractorEvaluation.HashableArguments;
+import org.apache.ctakes.typesystem.type.relation.CollectionTextRelation;
+import org.apache.ctakes.typesystem.type.relation.CollectionTextRelationIdentifiedAnnotationRelation;
+import org.apache.ctakes.typesystem.type.relation.CoreferenceRelation;
+import org.apache.ctakes.typesystem.type.syntax.ConllDependencyNode;
+import org.apache.ctakes.typesystem.type.textsem.AnatomicalSiteMention;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.ctakes.typesystem.type.textsem.Markable;
+import org.apache.ctakes.typesystem.type.textsem.MedicationEventMention;
+import org.apache.ctakes.typesystem.type.textspan.Paragraph;
+import org.apache.ctakes.typesystem.type.textspan.Segment;
+import org.apache.ctakes.typesystem.type.textspan.Sentence;
+import org.apache.log4j.Logger;
+import org.apache.uima.analysis_engine.AnalysisEngineDescription;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.descriptor.ConfigurationParameter;
+import org.apache.uima.fit.factory.AnalysisEngineFactory;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.apache.uima.jcas.cas.EmptyFSList;
+import org.apache.uima.jcas.cas.NonEmptyFSList;
+import org.apache.uima.jcas.tcas.Annotation;
+import org.apache.uima.resource.ResourceInitializationException;
+import org.cleartk.ml.CleartkAnnotator;
+import org.cleartk.ml.CleartkProcessingException;
+import org.cleartk.ml.DataWriter;
+import org.cleartk.ml.Feature;
+import org.cleartk.ml.feature.extractor.CleartkExtractorException;
+import org.cleartk.ml.feature.extractor.FeatureExtractor1;
+import org.cleartk.ml.jar.DefaultDataWriterFactory;
+import org.cleartk.ml.jar.DirectoryDataWriterFactory;
+import org.cleartk.ml.jar.GenericJarClassifierFactory;
+import org.cleartk.ml.svmlight.rank.QidInstance;
+import org.cleartk.util.ViewUriUtil;
+
+public class MentionClusterRankingCoreferenceAnnotator extends CleartkAnnotator<Double> {
+ public static final String NO_RELATION_CATEGORY = "-NONE-";
+ public static final String CLUSTER_RELATION_CATEGORY = "CoreferenceClusterMember";
+
+ public static final String PARAM_PROBABILITY_OF_KEEPING_A_NEGATIVE_EXAMPLE =
+ "ProbabilityOfKeepingANegativeExample";
+ @ConfigurationParameter(
+ name = PARAM_PROBABILITY_OF_KEEPING_A_NEGATIVE_EXAMPLE,
+ mandatory = false,
+ description = "probability that a negative example should be retained for training")
+ protected double probabilityOfKeepingANegativeExample = 0.5;
+
+ protected Random coin = new Random(0);
+
+ boolean greedyFirst = true;
+
+ private int qid = 0;
+
+ public static AnalysisEngineDescription createDataWriterDescription(
+ Class<? extends DataWriter<?>> dataWriterClass,
+ File outputDirectory,
+ float downsamplingRate) throws ResourceInitializationException {
+ return AnalysisEngineFactory.createEngineDescription(
+ MentionClusterRankingCoreferenceAnnotator.class,
+ CleartkAnnotator.PARAM_IS_TRAINING,
+ true,
+ MentionClusterRankingCoreferenceAnnotator.PARAM_PROBABILITY_OF_KEEPING_A_NEGATIVE_EXAMPLE,
+ downsamplingRate,
+ DefaultDataWriterFactory.PARAM_DATA_WRITER_CLASS_NAME,
+ dataWriterClass,
+ DirectoryDataWriterFactory.PARAM_OUTPUT_DIRECTORY,
+ outputDirectory);
+ }
+
+ public static AnalysisEngineDescription createAnnotatorDescription(
+ String modelPath) throws ResourceInitializationException {
+ return AnalysisEngineFactory.createEngineDescription(
+ MentionClusterRankingCoreferenceAnnotator.class,
+ CleartkAnnotator.PARAM_IS_TRAINING,
+ false,
+ GenericJarClassifierFactory.PARAM_CLASSIFIER_JAR_PATH,
+ modelPath);
+ }
+
+ private List<RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation>> relationExtractors = this.getFeatureExtractors();
+ private List<FeatureExtractor1<Markable>> mentionExtractors = this.getMentionExtractors();
+
+ private Set<String> markableStrings = null;
+ private Map<ConllDependencyNode,Collection<IdentifiedAnnotation>> nodeEntMap = null;
+ private Map<String,Set<Markable>> headWordMarkables = null;
+ private Map<HashableArguments,Double> pairScores = null;
+
+ protected List<RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation>> getFeatureExtractors() {
+ List<RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation>> extractors = new ArrayList<>();
+ extractors.add(new MentionClusterAgreementFeaturesExtractor());
+ extractors.add(new MentionClusterStringFeaturesExtractor());
+ extractors.add(new MentionClusterSectionFeaturesExtractor());
+ extractors.add(new MentionClusterUMLSFeatureExtractor());
+ extractors.add(new MentionClusterDepHeadExtractor());
+ extractors.add(new MentionClusterStackFeaturesExtractor());
+ extractors.add(new MentionClusterSalienceFeaturesExtractor());
+// extractors.add(new MentionClusterDistanceFeaturesExtractor());
+ extractors.add(new MentionClusterAttributeFeaturesExtractor());
+
+ try {
+ extractors.add(new MentionClusterDistSemExtractor());
+ extractors.add(new MentionClusterSemTypeDepPrefsFeatureExtractor());
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+
+ return extractors;
+ }
+
+ protected List<FeatureExtractor1<Markable>> getMentionExtractors(){
+ List<FeatureExtractor1<Markable>> extractors = new ArrayList<>();
+ // mention features from pairwise system:
+ extractors.add(new MentionClusterAgreementFeaturesExtractor());
+ extractors.add(new MentionClusterSectionFeaturesExtractor());
+ extractors.add(new MentionClusterUMLSFeatureExtractor());
+ extractors.add(new MentionClusterDepHeadExtractor());
+ extractors.add(new MentionClusterSalienceFeaturesExtractor());
+
+ try {
+ extractors.add(new MentionClusterMentionFeaturesExtractor());
+ } catch (CleartkExtractorException e) {
+ e.printStackTrace();
+ }
+ extractors.add(new MentionClusterAttributeFeaturesExtractor());
+
+ return extractors;
+ }
+
+ protected Iterable<CollectionTextRelationIdentifiedAnnotationPair> getCandidateRelationArgumentPairs(
+ JCas jcas,
+ IdentifiedAnnotation mention){
+ int sentDist = 5;
+ // using linked hash set ensures no duplicates:
+ LinkedHashSet<CollectionTextRelationIdentifiedAnnotationPair> pairs = new LinkedHashSet<>();
+ pairs.addAll(getSentenceDistancePairs(jcas, mention, sentDist));
+ pairs.addAll(getSectionHeaderPairs(jcas, mention, sentDist));
+ pairs.addAll(getClusterPairs(jcas, mention, Integer.MAX_VALUE));
+ pairs.addAll(getHeadwordMatchPairs(jcas, mention, sentDist));
+
+ return pairs;
+ }
+
+ /*
+ * getExactStringMatchPairs()
+ * For mentions that have the exact string repeated elsewhere in the document we want to
+ * allow matching across any distance. We don't use the sentence distance parameter here.
+ * We make use of a global variable markableStrings that is a HashSet containig all the markable
+ * strings from this document.
+ */
+ private List<CollectionTextRelationIdentifiedAnnotationPair> getExactStringMatchPairs(
+ JCas jcas, IdentifiedAnnotation mention, int sentDist) {
+ List<CollectionTextRelationIdentifiedAnnotationPair> pairs = new ArrayList<>();
+
+ if(markableStrings.contains(mention.getCoveredText().toLowerCase())){
+ for(CollectionTextRelation cluster : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ Annotation mostRecent = ClusterUtils.getMostRecent((NonEmptyFSList)cluster.getMembers(), mention);
+ if(mostRecent == null) continue;
+
+ for(Markable m : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ if(m == mostRecent) break;
+ // see if any of the members of the cluster have the exact same string as this
+ if(m.getCoveredText().toLowerCase().equals(mention.getCoveredText().toLowerCase())){
+ pairs.add(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ break;
+ }
+ }
+ }
+ }
+ return pairs;
+ }
+
+ /*
+ * getClusterPairs()
+ * In this method we allow to link to clusters containing more than one mention even if they
+ * are beyond a sentence distance. First we check whether the most recent mention in the cluster
+ * is within the specified sentence distance (presumably longer than the sentence distance passed into
+ * the method that constrains by distance). The wrinkle is that during training many clusters will have multiple
+ * members but only one before the focus mention. So we need to count the members of a cluster until we
+ * get to the most recent one in the cluster. If that value is > 1 then we allow the pairing.
+ */
+ private List<CollectionTextRelationIdentifiedAnnotationPair> getClusterPairs(
+ JCas jcas, IdentifiedAnnotation mention, int sentDist) {
+ List<CollectionTextRelationIdentifiedAnnotationPair> pairs = new ArrayList<>();
+ for(CollectionTextRelation cluster : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ NonEmptyFSList members = ((NonEmptyFSList)cluster.getMembers());
+ Annotation first = (Annotation) members.getHead();
+ if(first == null || mention.getBegin() <= first.getEnd()){
+ continue;
+ }
+
+ IdentifiedAnnotation mostRecent = (IdentifiedAnnotation) ClusterUtils.getMostRecent((NonEmptyFSList)cluster.getMembers(), mention);
+ if(mostRecent == null || EventCoreferenceAnnotator.sentDist(jcas, mostRecent, mention) > sentDist){
+ continue;
+ }
+ int numMembers=0;
+ for(Markable m : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ numMembers++;
+ if(m == mostRecent) break;
+ }
+ if(numMembers > 1){
+ pairs.add(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ }
+ }
+
+ return pairs;
+ }
+
+ /*
+ * Here we want to add only things that are nearby. First we check the semantic types
+ * of the cluster we're comparing against. If any member is an Anatomical Site or Medication,
+ * we add the cluster no matter what. Otherwise we check how many sentences are in between
+ * the mention and the latest element of the cluster.
+ */
+ protected List<CollectionTextRelationIdentifiedAnnotationPair> getSentenceDistancePairs(JCas jcas, IdentifiedAnnotation mention, int sentDist){
+ List<CollectionTextRelationIdentifiedAnnotationPair> pairs = new ArrayList<>();
+ Set<String> bestAnaTypes = getBestEnt(jcas, (Markable) mention);
+
+ for(CollectionTextRelation cluster : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ NonEmptyFSList members = ((NonEmptyFSList)cluster.getMembers());
+ Annotation first = (Annotation) members.getHead();
+ if(first == null || mention.getBegin() <= first.getEnd()) continue;
+
+ // check for distance if they are not anatomical site or medication
+ if(!(bestAnaTypes.contains(AnatomicalSiteMention.class.getSimpleName()) ||
+ bestAnaTypes.contains(MedicationEventMention.class.getSimpleName()))){
+
+ IdentifiedAnnotation mostRecent = (IdentifiedAnnotation) ClusterUtils.getMostRecent(members, mention);
+ if(mostRecent == null || EventCoreferenceAnnotator.sentDist(jcas, mostRecent, mention) > sentDist) continue;
+ }
+
+ // check for types of cluster
+ Set<String> bestClusterTypes = getBestEnt(jcas, cluster);
+ if(bestAnaTypes.size() > 0 && bestClusterTypes.size() > 0){
+ boolean overlap = false;
+ for(String semType : bestAnaTypes){
+ if(bestClusterTypes.contains(semType)){
+ overlap = true;
+ }
+ }
+ // they both correspond to named entities but no overlap in which category of named entity.
+ if(!overlap){
+ continue;
+ }
+ }
+ pairs.add(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ }
+ return pairs;
+ }
+
+ /*
+ * getSectionHeaderPairs()
+ * Here we want to add clusters where one of the members is on a line all by itself (a section header)
+ * To do this we leverage the annotatino of Paragraphs, roughly the areas between newlines. If such a
+ * span only contains one sentence then we consider it a "header" (or also as important a list item).
+ * If it is a header we add it. Here we use sentDist to not bother adding things that will be added by
+ * the "sentence distance" method.
+ */
+ protected List<CollectionTextRelationIdentifiedAnnotationPair> getSectionHeaderPairs(JCas jcas, IdentifiedAnnotation mention, int sentDist){
+ List<CollectionTextRelationIdentifiedAnnotationPair> pairs = new ArrayList<>();
+ for(CollectionTextRelation cluster : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ NonEmptyFSList members = ((NonEmptyFSList)cluster.getMembers());
+ Annotation first = (Annotation) members.getHead();
+ if(first == null || mention.getBegin() <= first.getEnd()){
+ continue;
+ }
+
+ // first check if it is sentence distance range -- if so we can ignore because it will be include by other pair generator
+ IdentifiedAnnotation mostRecent = (IdentifiedAnnotation) ClusterUtils.getMostRecent(members, mention);
+ if(mostRecent == null || EventCoreferenceAnnotator.sentDist(jcas, mostRecent, mention) <= sentDist){
+ continue;
+ }
+
+ // now check if any of the mentions are in a section header
+ List<Paragraph> pars = JCasUtil.selectCovered(jcas, Paragraph.class, 0, mention.getBegin());
+ for(int j = 0; j < pars.size(); j++){
+ boolean match = false;
+ Paragraph par = pars.get(j); // pars.get(pars.size()-j-1);
+ List<Sentence> coveredSents = JCasUtil.selectCovered(jcas, Sentence.class, par);
+ if(coveredSents != null && coveredSents.size() == 1){
+ // this is sentences that are the same span as paragraphs -- how we model section headers
+ // see if any of the cluster mentions are in the section header
+ for(Markable m : JCasUtil.select(members, Markable.class)){
+ if(dominates(par, m)){
+ pairs.add(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ match = true;
+ break;
+ }
+ }
+ }
+ if(match) break;
+ }
+ }
+ return pairs;
+ }
+
+ protected List<CollectionTextRelationIdentifiedAnnotationPair> getHeadwordMatchPairs(JCas jcas, IdentifiedAnnotation mention, int sentDist){
+ List<CollectionTextRelationIdentifiedAnnotationPair> pairs = new ArrayList<>();
+
+ ConllDependencyNode headNode = DependencyUtility.getNominalHeadNode(jcas, mention);
+ if(headNode == null){
+ Logger.getLogger(MentionClusterRankingCoreferenceAnnotator.class).warn("There is a markable with no dependency node covering it.");
+ return pairs;
+ }
+ String head = headNode.getCoveredText().toLowerCase();
+ if(headWordMarkables.containsKey(head)){
+ Set<Markable> headSet = headWordMarkables.get(head);
+ for(CollectionTextRelation cluster : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ Annotation mostRecent = ClusterUtils.getMostRecent((NonEmptyFSList)cluster.getMembers(), mention);
+ if(mostRecent == null) continue;
+ for(Markable m : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ if(headSet.contains(mostRecent)){
+ pairs.add(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ break;
+ }
+ if(m == mostRecent) break;
+ }
+ }
+ }
+
+ return pairs;
+ }
+
+ @Override
+ public void process(JCas jCas) throws AnalysisEngineProcessException {
+ // lookup from pair of annotations to binary text relation
+ // note: assumes that there will be at most one relation per pair
+ markableStrings = new HashSet<>();
+ nodeEntMap = JCasUtil.indexCovering(jCas, ConllDependencyNode.class, IdentifiedAnnotation.class);
+ headWordMarkables = new HashMap<>();
+// pairScores = getMarkablePairScores(jCas);
+
+ Map<CollectionTextRelationIdentifiedAnnotationPair, CollectionTextRelationIdentifiedAnnotationRelation> relationLookup;
+ relationLookup = new HashMap<>();
+ if (this.isTraining()) {
+ for (CollectionTextRelation cluster : JCasUtil.select(jCas, CollectionTextRelation.class)) {
+ for(IdentifiedAnnotation mention : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ CollectionTextRelationIdentifiedAnnotationRelation relation =
+ new CollectionTextRelationIdentifiedAnnotationRelation(jCas);
+ relation.setCluster(cluster);
+ relation.setMention(mention);
+ relation.setCategory("CoreferenceClusterMember");
+ relation.addToIndexes();
+ // The key is a list of args so we can do bi-directional lookup
+ CollectionTextRelationIdentifiedAnnotationPair key = new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention);
+ if(relationLookup.containsKey(key)){
+ String cat = relationLookup.get(key).getCategory();
+ System.err.println("Error in: "+ ViewUriUtil.getURI(jCas).toString());
+ System.err.println("Error! This attempted relation " + relation.getCategory() + " already has a relation " + cat + " at this span: " + mention.getCoveredText());
+ }
+ relationLookup.put(key, relation);
+ }
+ }
+ }
+
+
+ for(Segment segment : JCasUtil.select(jCas, Segment.class)){
+ for(Markable mention : JCasUtil.selectCovered(jCas, Markable.class, segment)){
+ ConllDependencyNode headNode = DependencyUtility.getNominalHeadNode(jCas, mention);
+ String mentionText = mention.getCoveredText().toLowerCase();
+ boolean singleton = true;
+ double maxScore = Double.NEGATIVE_INFINITY;
+ CollectionTextRelation maxCluster = null;
+ List<Feature> mentionFeatures = new ArrayList<>();
+ for(FeatureExtractor1<Markable> extractor : this.mentionExtractors){
+ mentionFeatures.addAll(extractor.extract(jCas, mention));
+ }
+
+ for(CollectionTextRelationIdentifiedAnnotationPair pair : this.getCandidateRelationArgumentPairs(jCas, mention)){
+ CollectionTextRelation cluster = pair.getCluster();
+ // apply all the feature extractors to extract the list of features
+ List<Feature> features = new ArrayList<>();
+ features.addAll(mentionFeatures);
+
+ for (RelationFeaturesExtractor<CollectionTextRelation,IdentifiedAnnotation> extractor : this.relationExtractors) {
+ List<Feature> feats = extractor.extract(jCas, cluster, mention);
+ if (feats != null){
+// Logger.getRootLogger().info(String.format("For cluster with %d mentions, %d %s features", JCasUtil.select(cluster.getMembers(), Markable.class).size(), feats.size(), extractor.getClass().getSimpleName()));
+ features.addAll(feats);
+ }
+ }
+
+
+ // here is where feature conjunctions can go (dupFeatures)
+ List<Feature> dupFeatures = new ArrayList<>();
+ // sanity check on feature values
+ for (Feature feature : features) {
+ if (feature.getValue() == null) {
+ feature.setValue("NULL");
+ String message = String.format("Null value found in %s from %s", feature, features);
+ System.err.println(message);
+ // throw new IllegalArgumentException(String.format(message, feature, features));
+ }else{
+ String prefix = null;
+// if(mentionText.equals("it") || mentionText.equals("this") || mentionText.equals("that")){
+// prefix = "PRO_"+mentionText;
+// }else if(headNode != null && headNode.getPostag() != null){
+// prefix = headNode.getPostag();
+// }else{
+// prefix = "UNK";
+// }
+ if(prefix != null){
+ dupFeatures.add(new Feature(prefix+"_"+feature.getName(), feature.getValue()));
+ }
+ }
+ }
+ features.addAll(dupFeatures);
+
+ // during training, feed the features to the data writer
+ // create a classification instance and write it to the training data
+
+ if (this.isTraining()) {
+ String category = this.getRelationCategory(relationLookup, cluster, mention);
+ if (category == null) {
+ continue;
+ }
+ double outVal = 1.0;
+ if(category.equals(NO_RELATION_CATEGORY)){
+ outVal = 0.0;
+ }
+
+ QidInstance<Double> inst = new QidInstance<>();
+ inst.setQid(String.valueOf(qid));
+ inst.addAll(features);
+ inst.setOutcome(outVal);
+ this.dataWriter.write(inst);
+ if(!category.equals(NO_RELATION_CATEGORY)){
+ singleton = false;
+ break;
+ }
+ }
+
+ // during classification feed the features to the classifier and create
+ // annotations
+ else {
+ Double prediction = this.classify(features);
+ if(prediction > maxScore){
+ maxScore = prediction;
+ maxCluster = cluster;
+ }
+ }
+ }
+
+ markableStrings.add(mention.getCoveredText().toLowerCase());
+
+ if(headNode != null){
+ String head = headNode.getCoveredText().toLowerCase();
+ if(!headWordMarkables.containsKey(head)){
+ headWordMarkables.put(head, new HashSet<Markable>());
+ }
+ headWordMarkables.get(head).add(mention);
+ }
+
+ if(this.isTraining()){
+ // write a dummy link with only mention features:
+ QidInstance<Double> inst = new QidInstance<>();
+ inst.setQid(String.valueOf(qid));
+ for(Feature feat : mentionFeatures){
+ if(feat.getName() != null){
+ feat.setName("DUMMYLINK_" + feat.getName());
+ }
+ }
+ inst.addAll(mentionFeatures);
+ if(singleton){
+ inst.setOutcome(1.0);
+ }else{
+ inst.setOutcome(0.0);
+ }
+ this.dataWriter.write(inst);
+ }else{
+ Double nullPrediction = this.classify(mentionFeatures);
+ if(nullPrediction > maxScore){
+ // make the markable it's own cluster:
+ CollectionTextRelation chain = new CollectionTextRelation(jCas);
+ NonEmptyFSList list = new NonEmptyFSList(jCas);
+ list.setHead(mention);
+ list.setTail(new EmptyFSList(jCas));
+ chain.setMembers(list);
+ chain.addToIndexes();
+ list.addToIndexes();
+ list.getTail().addToIndexes();
+ }else{
+ createRelation(jCas, maxCluster, mention, CLUSTER_RELATION_CATEGORY);
+ }
+ }
+ qid++;
+ }
+ }
+
+ removeSingletonClusters(jCas);
+ }
+
+ /**
+ * Looks up the arguments in the specified lookup table and converts the
+ * relation into a label for classification
+ *
+ * @return If this category should not be processed for training return
+ * <i>null</i> otherwise it returns the label sent to the datawriter
+ */
+ protected String getRelationCategory(
+ Map<CollectionTextRelationIdentifiedAnnotationPair, CollectionTextRelationIdentifiedAnnotationRelation> relationLookup,
+ CollectionTextRelation cluster,
+ IdentifiedAnnotation mention) {
+ CollectionTextRelationIdentifiedAnnotationRelation relation =
+ relationLookup.get(new CollectionTextRelationIdentifiedAnnotationPair(cluster, mention));
+ String category;
+ if (relation != null) {
+ category = relation.getCategory();
+ } else if (coin.nextDouble() <= this.probabilityOfKeepingANegativeExample) {
+ category = NO_RELATION_CATEGORY;
+ } else {
+ category = null;
+ }
+ return category;
+ }
+
+ /**
+ * Predict an outcome given a set of features. By default, this simply
+ * delegates to the object's <code>classifier</code>. Subclasses may override
+ * this method to implement more complex classification procedures.
+ *
+ * @param features
+ * The features to be classified.
+ * @return The predicted outcome (label) for the features.
+ */
+ protected Double classify(List<Feature> features) throws CleartkProcessingException {
+ return this.classifier.classify(features);
+ }
+
+ /**
+ * Create a UIMA relation type based on arguments and the relation label. This
+ * allows subclasses to create/define their own types: e.g. coreference can
+ * create CoreferenceRelation instead of BinaryTextRelation
+ *
+ * @param jCas
+ * - JCas object, needed to create new UIMA types
+ * @param arg1
+ * - First argument to relation
+ * @param arg2
+ * - Second argument to relation
+ * @param predictedCategory
+ * - Name of relation
+ */
+ protected void createRelation(
+ JCas jCas,
+ CollectionTextRelation cluster,
+ IdentifiedAnnotation mention,
+ String predictedCategory) {
+ // add the relation to the CAS
+ CollectionTextRelationIdentifiedAnnotationRelation relation = new CollectionTextRelationIdentifiedAnnotationRelation(jCas);
+ relation.setCluster(cluster);
+ relation.setMention(mention);
+ relation.setCategory(predictedCategory);
+ relation.addToIndexes();
+
+// RelationArgument arg = new RelationArgument(jCas);
+// arg.setArgument(mention);
+ ListFactory.append(jCas, cluster.getMembers(), mention);
+ }
+
+
+ private void removeSingletonClusters(JCas jcas){
+ List<CollectionTextRelation> toRemove = new ArrayList<>();
+ for(CollectionTextRelation rel : JCasUtil.select(jcas, CollectionTextRelation.class)){
+ NonEmptyFSList head = (NonEmptyFSList) rel.getMembers();
+ if(head.getTail() instanceof EmptyFSList){
+ toRemove.add(rel);
+ }
+ }
+
+ for(CollectionTextRelation rel : toRemove){
+ rel.removeFromIndexes();
+ }
+ }
+
+ private static final boolean dominates(Annotation arg1, Annotation arg2) {
+ return (arg1.getBegin() <= arg2.getBegin() && arg1.getEnd() >= arg2.getEnd());
+ }
+
+ public Set<String> getBestEnt(JCas jcas, CollectionTextRelation cluster){
+ Set<String> semTypes = new HashSet<>();
+ for(Markable member : JCasUtil.select(cluster.getMembers(), Markable.class)){
+ semTypes.addAll(getBestEnt(jcas, member));
+ }
+ return semTypes;
+ }
+
+ public Set<String> getBestEnt(JCas jcas, Markable markable){
+ Set<String> bestEnts = new HashSet<>();
+ IdentifiedAnnotation bestEnt = null;
+ Set<IdentifiedAnnotation> otherBestEnts = new HashSet<>();
+ ConllDependencyNode head = DependencyUtility.getNominalHeadNode(jcas, markable);
+ Collection<IdentifiedAnnotation> coveringEnts = nodeEntMap.get(head);
+ for(IdentifiedAnnotation ent : coveringEnts){
+ if(ent.getOntologyConceptArr() == null) continue; // skip non-umls entities.
+ ConllDependencyNode entHead = DependencyUtility.getNominalHeadNode(jcas, ent);
+ if(entHead == head){
+ if(bestEnt == null){
+ bestEnt = ent;
+ }else if((ent.getEnd()-ent.getBegin()) > (bestEnt.getEnd() - bestEnt.getBegin())){
+ // if the span of this entity is bigger than the biggest existing one:
+ bestEnt = ent;
+ otherBestEnts = new HashSet<>();
+ }else if((ent.getEnd()-ent.getBegin()) == (bestEnt.getEnd() - bestEnt.getBegin())){
+ // there is another one with the exact same span and possibly different type!
+ otherBestEnts.add(ent);
+ }
+ }
+ }
+
+ if(bestEnt!=null){
+ bestEnts.add(bestEnt.getClass().getSimpleName());
+ for(IdentifiedAnnotation other : otherBestEnts){
+ bestEnts.add(other.getClass().getSimpleName());
+ }
+ }
+ return bestEnts;
+ }
+
+
+ public Map<HashableArguments, Double> getMarkablePairScores(JCas jCas){
+ Map<HashableArguments, Double> scoreMap = new HashMap<>();
+ for(CoreferenceRelation reln : JCasUtil.select(jCas, CoreferenceRelation.class)){
+ HashableArguments pair = new HashableArguments((IdentifiedAnnotation)reln.getArg1().getArgument(), (IdentifiedAnnotation)reln.getArg2().getArgument());
+ scoreMap.put(pair, reln.getConfidence());
+ }
+ return scoreMap;
+ }
+
+ public static class CollectionTextRelationIdentifiedAnnotationPair {
+ private final CollectionTextRelation cluster;
+ private final IdentifiedAnnotation mention;
+
+ public CollectionTextRelationIdentifiedAnnotationPair(CollectionTextRelation cluster, IdentifiedAnnotation mention){
+ this.cluster = cluster;
+ this.mention = mention;
+ }
+
+ public final CollectionTextRelation getCluster(){
+ return this.cluster;
+ }
+
+ public final IdentifiedAnnotation getMention(){
+ return this.mention;
+ }
+
+ @Override
+ public boolean equals(Object obj) {
+ CollectionTextRelationIdentifiedAnnotationPair other = (CollectionTextRelationIdentifiedAnnotationPair) obj;
+ return (this.cluster == other.cluster &&
+ this.mention == other.mention);
+ }
+
+ @Override
+ public int hashCode() {
+ return 31*cluster.hashCode() + (mention==null ? 0 : mention.hashCode());
+ }
+ }
+
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/PersonChainAnnotator.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/PersonChainAnnotator.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/PersonChainAnnotator.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/PersonChainAnnotator.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,177 @@
+package org.apache.ctakes.coreference.ae;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.dependency.parser.util.DependencyUtility;
+import org.apache.ctakes.typesystem.type.relation.CollectionTextRelation;
+import org.apache.ctakes.typesystem.type.syntax.ConllDependencyNode;
+import org.apache.ctakes.typesystem.type.syntax.WordToken;
+import org.apache.ctakes.typesystem.type.textsem.Markable;
+import org.apache.uima.analysis_engine.AnalysisEngineDescription;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.component.JCasAnnotator_ImplBase;
+import org.apache.uima.fit.factory.AnalysisEngineFactory;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.apache.uima.jcas.cas.EmptyFSList;
+import org.apache.uima.jcas.cas.FSList;
+import org.apache.uima.jcas.cas.NonEmptyFSList;
+import org.apache.uima.resource.ResourceInitializationException;
+
+public class PersonChainAnnotator extends JCasAnnotator_ImplBase {
+
+ @Override
+ public void process(JCas jcas) throws AnalysisEngineProcessException {
+ NonEmptyFSList ptList = new NonEmptyFSList(jcas);
+ ptList.setHead(null);
+ NonEmptyFSList weList = new NonEmptyFSList(jcas);
+ weList.setHead(null);
+ NonEmptyFSList drList = new NonEmptyFSList(jcas);
+ drList.setHead(null);
+ List<NonEmptyFSList> otherDrs = new ArrayList<>();
+
+ List<WordToken> words = new ArrayList<>(JCasUtil.select(jcas, WordToken.class));
+ for(int i = 0; i < words.size(); i++){
+ WordToken word = words.get(i);
+ String text = word.getCoveredText();
+ if(word.getPartOfSpeech().startsWith("PRP")){
+ if(text.equalsIgnoreCase("I") || text.equalsIgnoreCase("me") || text.equalsIgnoreCase("my")){
+ Markable drMention = new Markable(jcas, word.getBegin(), word.getEnd());
+ addToList(jcas, drList, drMention);
+ }else if(text.equalsIgnoreCase("we") || text.equalsIgnoreCase("us") || text.equalsIgnoreCase("our")){
+ Markable weMention = new Markable(jcas, word.getBegin(), word.getEnd());
+ addToList(jcas, weList, weMention);
+ }else if(text.equalsIgnoreCase("it")){
+ // do nothing
+ }else{
+ Markable ptMention = new Markable(jcas, word.getBegin(), word.getEnd());
+ addToList(jcas, ptList, ptMention);
+ }
+ }else if(text.equalsIgnoreCase("dr.")){
+ Markable drMention = getDoctorMarkable(jcas, word); //new Markable(jcas, word.getBegin(), words.get(i+1).getEnd());
+ addToList(jcas, getCorrectDoctor(jcas, drMention, otherDrs), drMention);
+ }else if(text.equalsIgnoreCase("mrs.") || text.equalsIgnoreCase("mr.") || text.equalsIgnoreCase("ms.")){
+ // TODO - smarter logic for Dr. Firstname Lastname
+ Markable ptMention = new Markable(jcas, word.getBegin(), words.get(i+1).getEnd());
+ addToList(jcas, ptList, ptMention);
+ }else if(text.equalsIgnoreCase("patient") || text.equalsIgnoreCase("pt")){
+ Markable ptMention = new Markable(jcas, word.getBegin(), word.getEnd());
+ addToList(jcas, ptList, ptMention);
+ }
+ }
+
+ for(NonEmptyFSList otherDr : otherDrs){
+ if(otherDr.getHead() != null){
+ if(otherDr.getTail() != null){
+ endList(jcas, otherDr);
+ CollectionTextRelation drChain = new CollectionTextRelation(jcas);
+ drChain.setMembers(otherDr);
+ drChain.addToIndexes();
+ }
+ }
+ }
+
+ if(drList.getHead() != null && drList.getTail() != null){
+ endList(jcas, drList);
+ CollectionTextRelation drChain = new CollectionTextRelation(jcas);
+ drChain.setMembers(drList);
+ drChain.addToIndexes();
+ }
+ if(ptList.getHead() != null && ptList.getTail() != null){
+ endList(jcas, ptList);
+ CollectionTextRelation ptChain = new CollectionTextRelation(jcas);
+ ptChain.setMembers(ptList);
+ ptChain.addToIndexes();
+ }
+ if(weList.getHead() != null && weList.getTail() != null){
+ endList(jcas, weList);
+ CollectionTextRelation weChain = new CollectionTextRelation(jcas);
+ weChain.setMembers(weList);
+ weChain.addToIndexes();
+ }
+ }
+
+ public static AnalysisEngineDescription createAnnotatorDescription() throws ResourceInitializationException {
+ return AnalysisEngineFactory.createEngineDescription(PersonChainAnnotator.class);
+ }
+
+ private static void addToList(JCas jcas, NonEmptyFSList list, Markable arg){
+ arg.addToIndexes();
+ if(list.getHead() == null){
+ // first list element:
+ list.setHead(arg);
+ }else{
+ // subsequent list elements:
+ NonEmptyFSList cur = list;
+ while(cur.getTail() != null){
+ cur = (NonEmptyFSList)cur.getTail();
+ }
+ NonEmptyFSList tail = new NonEmptyFSList(jcas);
+ tail.setHead(arg);
+ cur.setTail(tail);
+ tail.addToIndexes();
+ }
+ }
+
+ private static void endList(JCas jcas, NonEmptyFSList list){
+ NonEmptyFSList cur = list;
+ while(cur.getTail() != null){
+ cur = (NonEmptyFSList)cur.getTail();
+ }
+ EmptyFSList tail = new EmptyFSList(jcas);
+ cur.setTail(tail);
+ tail.addToIndexes();
+ }
+
+ private static NonEmptyFSList getCorrectDoctor(JCas jcas, Markable mention, List<NonEmptyFSList> drLists){
+ NonEmptyFSList correctDr = null;
+ if(mention.getCoveredText().length() < 5){
+ if(drLists.size() > 0){
+ correctDr = drLists.get(0);
+ }
+ }else{
+ String nameText = mention.getCoveredText().substring(4);
+ for(NonEmptyFSList drList : drLists){
+ FSList curNode = drList;
+ do{
+ String otherName = ((Markable)((NonEmptyFSList)curNode).getHead()).getCoveredText();
+ if(otherName.length() >= 5){
+ otherName = otherName.substring(4);
+ if(otherName.contains(nameText) || nameText.contains(otherName)){
+ correctDr = drList;
+ }
+ }
+ curNode = ((NonEmptyFSList)curNode).getTail();
+ }while(curNode instanceof NonEmptyFSList);
+ if(correctDr != null) break;
+ }
+ }
+ if(correctDr == null){
+ correctDr = new NonEmptyFSList(jcas);
+ correctDr.setHead(null);
+ drLists.add(correctDr);
+ }
+ return correctDr;
+ }
+
+ private static Markable getDoctorMarkable(JCas jcas, WordToken drToken){
+ Markable markable = null;
+
+ ConllDependencyNode nnpHead = DependencyUtility.getDependencyNode(jcas, drToken);
+ try{
+ while(nnpHead != null && nnpHead.getHead() != null && nnpHead.getHead().getId() != 0 && nnpHead.getHead().getPostag().equals("NNP")){
+ nnpHead = nnpHead.getHead();
+ }
+ }catch(NullPointerException e){
+ System.err.print(".");
+ }
+
+ int start = drToken.getBegin();
+ int end = nnpHead.getEnd();
+ if(end < start) end = drToken.getEnd();
+
+ markable = new Markable(jcas, start, end);
+ return markable;
+ }
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/AttributeFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/AttributeFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/AttributeFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/AttributeFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,65 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import static org.apache.ctakes.coreference.ae.features.TokenFeatureExtractor.isGeneric;
+import static org.apache.ctakes.coreference.ae.features.TokenFeatureExtractor.isHistory;
+import static org.apache.ctakes.coreference.ae.features.TokenFeatureExtractor.isNegated;
+import static org.apache.ctakes.coreference.ae.features.TokenFeatureExtractor.isPatient;
+import static org.apache.ctakes.coreference.ae.features.TokenFeatureExtractor.isUncertain;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.ctakes.typesystem.type.textsem.TimeMention;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.apache.uima.jcas.tcas.Annotation;
+import org.cleartk.ml.Feature;
+
+public class AttributeFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation, IdentifiedAnnotation> {
+
+ @Override
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation ante, IdentifiedAnnotation ana)
+ throws AnalysisEngineProcessException {
+ List<Feature> features = new ArrayList<>();
+
+ boolean anaNegated = isNegated(ana);
+ features.add(new Feature("MC_ana_NEGATED", anaNegated));
+ boolean anaUncertain = isUncertain(ana);
+ features.add(new Feature("MC_ana_UNCERTAIN", anaUncertain));
+ boolean anaGen = isGeneric(ana);
+ features.add(new Feature("MC_ana_GENERIC", anaGen));
+ boolean anaSubj = isPatient(ana);
+ features.add(new Feature("MC_ana_PATIENT", anaSubj));
+ boolean anaHist = isHistory(ana);
+ features.add(new Feature("MC_ana_HISTORY", anaHist));
+ boolean anaTimex = isTimex(ana);
+ features.add(new Feature("MC_ana_TIMEX", anaTimex));
+
+ boolean anteNegated = isNegated(ante);
+ features.add(new Feature("MC_ante_NEGATED", anteNegated));
+ boolean anteUncertain = isUncertain(ante);
+ features.add(new Feature("MC_ante_UNCERTAIN", anteUncertain));
+ boolean anteGen = isGeneric(ante);
+ features.add(new Feature("MC_ante_GENERIC", anteGen));
+ boolean anteSubj = isPatient(ante);
+ features.add(new Feature("MC_ante_PATIENT", anteSubj));
+ boolean anteHist = isHistory(ante);
+ features.add(new Feature("MC_ante_HISTORY", anteHist));
+ boolean anteTimex = isTimex(ante);
+ features.add(new Feature("MC_ante_TIMEX", anteTimex));
+
+ features.add(new Feature("MC_AGREE_NEG", anteNegated == anaNegated));
+ features.add(new Feature("MC_AGREE_UNC", anteUncertain == anaUncertain));
+ features.add(new Feature("MC_AGREE_TIMEX", anteTimex == anaTimex));
+
+ return features;
+ }
+
+ private static boolean isTimex(Annotation a){
+ return JCasUtil.selectCovered(TimeMention.class, a).size() > 0;
+ }
+
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/CorefSyntaxFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/CorefSyntaxFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/CorefSyntaxFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/CorefSyntaxFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,32 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.dependency.parser.util.DependencyUtility;
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.syntax.ConllDependencyNode;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.jcas.JCas;
+import org.cleartk.ml.Feature;
+
+public class CorefSyntaxFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation,IdentifiedAnnotation> {
+
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation arg1,
+ IdentifiedAnnotation arg2) throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+
+ ConllDependencyNode head1 = DependencyUtility.getNominalHeadNode(jCas, arg1);
+ ConllDependencyNode head2 = DependencyUtility.getNominalHeadNode(jCas, arg2);
+
+ if(head1 != null){
+ feats.add(new Feature("Arg1Head", head1.getCoveredText().toLowerCase()));
+ }
+ if(head2 != null){
+ feats.add(new Feature("Arg2Head", head2.getCoveredText().toLowerCase()));
+ }
+ return feats;
+ }
+
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistSemFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistSemFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistSemFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistSemFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,106 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.io.FileNotFoundException;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.List;
+
+import org.apache.ctakes.core.resource.FileLocator;
+import org.apache.ctakes.dependency.parser.util.DependencyUtility;
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.syntax.BaseToken;
+import org.apache.ctakes.typesystem.type.syntax.ConllDependencyNode;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.ctakes.utils.distsem.WordEmbeddings;
+import org.apache.ctakes.utils.distsem.WordVector;
+import org.apache.ctakes.utils.distsem.WordVectorReader;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.jcas.JCas;
+import org.cleartk.ml.Feature;
+import org.apache.uima.fit.util.JCasUtil;
+
+public class DistSemFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation,IdentifiedAnnotation> {
+
+ // default value is 0.5 (rather than 0.0) because we don't want to assume OOV words are dissimilar
+ public static final double DEFAULT_SIM = 0.5;
+
+ private WordEmbeddings words = null;
+
+ public DistSemFeatureExtractor() throws FileNotFoundException, IOException{
+ words = WordVectorReader.getEmbeddings(FileLocator.getAsStream("org/apache/ctakes/coreference/distsem/mimic_vectors.txt"));
+ }
+
+ @Override
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation arg1,
+ IdentifiedAnnotation arg2) throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+
+ double sim = 0.0;
+// double[] a1vec = getArgVector(arg1);
+// double[] a2vec = getArgVector(arg2);
+//
+// if(a1vec != null && a2vec != null){
+// for(int i = 0; i < a1vec.length; i++){
+// sim += a1vec[i] * a2vec[i];
+// }
+// }else{
+// sim = DEFAULT_SIM;
+// }
+//
+// assert !Double.isNaN(sim);
+//
+// feats.add(new Feature("ARG_SIMILARITY_WORD2VEC", sim));
+
+ ConllDependencyNode node1 = DependencyUtility.getNominalHeadNode(jCas, arg1);
+ ConllDependencyNode node2 = DependencyUtility.getNominalHeadNode(jCas, arg2);
+ String head1 = node1 != null ? node1.getCoveredText().toLowerCase() : null;
+ String head2 = node2 != null ? node2.getCoveredText().toLowerCase() : null;
+ if(head1 != null && head2 != null && words.containsKey(head1) && words.containsKey(head2)){
+ sim = words.getSimilarity(head1, head2);
+ }else{
+ sim = DEFAULT_SIM;
+ }
+ feats.add(new Feature("HEAD_SIMILARITY_WORD2VEC", sim));
+
+ return feats;
+ }
+
+
+ @SuppressWarnings("unused")
+ private double[] getArgVector(IdentifiedAnnotation arg){
+ double[] vec = null;
+
+ Collection<BaseToken> tokens = JCasUtil.selectCovered(BaseToken.class, arg);
+
+ for(BaseToken token : tokens){
+ WordVector wv = words.getVector(token.getCoveredText());
+ if(wv == null){
+ wv = words.getVector(token.getCoveredText().toLowerCase());
+ }
+ if(wv != null){
+ if(vec == null){
+ vec = new double[wv.size()];
+ Arrays.fill(vec, 0.0);
+ }
+ for(int i = 0; i < vec.length; i++){
+ vec[i] += wv.getValue(i);
+ }
+ }
+ }
+
+ if(vec != null){
+ double len = 0.0;
+ for(int i = 0; i < vec.length; i++){
+ len += vec[i]*vec[i];
+ }
+ len = Math.sqrt(len);
+ assert !Double.isNaN(len);
+ for(int i = 0; i < vec.length; i++){
+ vec[i] /= len;
+ }
+ }
+ return vec;
+ }
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistanceFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistanceFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistanceFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/DistanceFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,29 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.coreference.util.CorefConsts;
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.syntax.BaseToken;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.ctakes.typesystem.type.textspan.Sentence;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.jcas.JCas;
+import org.cleartk.ml.Feature;
+import org.apache.uima.fit.util.JCasUtil;
+
+public class DistanceFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation,IdentifiedAnnotation> {
+
+ @Override
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation arg1,
+ IdentifiedAnnotation arg2) throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+ feats.add(new Feature("TOK_DIST",
+ JCasUtil.selectCovered(jCas, BaseToken.class, arg1.getBegin(), arg2.getEnd()).size() / (double)CorefConsts.TOKDIST));
+ feats.add(new Feature("SENT_DIST",
+ JCasUtil.selectCovered(jCas, Sentence.class, arg1.getBegin(), arg2.getEnd()).size() / (double) CorefConsts.NEDIST));
+ return feats;
+ }
+
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SalienceFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SalienceFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SalienceFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SalienceFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,24 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.jcas.JCas;
+import org.cleartk.ml.Feature;
+
+public class SalienceFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation, IdentifiedAnnotation> {
+
+ @Override
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation ante, IdentifiedAnnotation ana)
+ throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+
+ feats.add(new Feature("MP_ANTE_SALIENCE", ante.getConfidence()));
+ feats.add(new Feature("MP_ANA_SALIENCE", ana.getConfidence()));
+ return feats;
+ }
+
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SectionFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SectionFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SectionFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/SectionFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,56 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.ctakes.typesystem.type.textspan.Paragraph;
+import org.apache.ctakes.typesystem.type.textspan.Sentence;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.cleartk.ml.Feature;
+
+public class SectionFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation,IdentifiedAnnotation> {
+
+ public List<Feature> extract(JCas jcas, IdentifiedAnnotation ante,
+ IdentifiedAnnotation ana) throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+ boolean anteInHeader = false;
+ boolean anaInHeader = false;
+ int antePar = -1;
+ int anaPar = -1;
+
+ // Find section headers -- paragraphs
+ List<Paragraph> pars = new ArrayList<>(JCasUtil.select(jcas, Paragraph.class));
+ for(int i = 0; i < pars.size(); i++){
+ Paragraph par = pars.get(i);
+ if(par.getBegin() > ana.getEnd()){
+ break;
+ }
+ if(ante.getBegin() >= par.getBegin() && ante.getEnd() <= par.getEnd()){
+ antePar = i;
+ }
+ if(ana.getBegin() >= par.getBegin() && ana.getEnd() <= par.getEnd()){
+ anaPar = i;
+ }
+ List<Sentence> coveredSents = JCasUtil.selectCovered(jcas, Sentence.class, par);
+ if(coveredSents != null && coveredSents.size() == 1){
+ if(antePar == i){
+ anteInHeader = true;
+ }
+ if(anaPar == i){
+ anaInHeader = true;
+ }
+ }
+ }
+
+ feats.add(new Feature("AnteInHeader", anteInHeader));
+ feats.add(new Feature("AnaInHeader", anaInHeader));
+ if(anteInHeader && antePar+1 == anaPar){
+ feats.add(new Feature("AnteHeaderHeadsAna", true));
+ }
+ return feats;
+ }
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/StringMatchingFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/StringMatchingFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/StringMatchingFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/StringMatchingFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,141 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.util.ArrayList;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Set;
+
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.syntax.BaseToken;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.apache.uima.jcas.tcas.Annotation;
+import org.cleartk.ml.Feature;
+
+public class StringMatchingFeatureExtractor implements
+ RelationFeaturesExtractor<IdentifiedAnnotation,IdentifiedAnnotation> {
+
+ @Override
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation arg1,
+ IdentifiedAnnotation arg2) throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+
+ // don't extract sim features if one of the markables is a pronoun
+ if(isPronoun(arg1) || isPronoun(arg2)) return feats;
+
+ String s1 = arg1.getCoveredText();
+ String s2 = arg2.getCoveredText();
+ Set<String> words1 = contentWords(arg1);
+ Set<String> words2 = contentWords(arg2);
+
+ feats.add(new Feature("MATCH_EXACT",
+ s1.equalsIgnoreCase(s2)));
+ feats.add(new Feature("MATCH_START",
+ startMatch(s1,s2)));
+ feats.add(new Feature("MATCH_END",
+ endMatch(s1,s2)));
+ feats.add(new Feature("MATCH_SOON",
+ soonMatch(s1,s2)));
+ feats.add(new Feature("MATCH_OVERLAP",
+ wordOverlap(words1, words2)));
+ feats.add(new Feature("MATCH_SUBSTRING",
+ wordSubstring(words1, words2)));
+ return feats;
+ }
+
+ public static boolean startMatch (String a, String b) {
+ int ia = a.indexOf(" ");
+ int ib = b.indexOf(" ");
+ String aa = a.substring(0, ia==-1?(a.length()>5?5:a.length()):ia);
+ String bb = b.substring(0, ib==-1?(b.length()>5?5:b.length()):ib);
+ return aa.equalsIgnoreCase(bb);
+ }
+
+ public static boolean endMatch (String a, String b) {
+ int ia = a.lastIndexOf(" ");
+ int ib = b.lastIndexOf(" ");
+ String aa = a.substring(ia==-1?(a.length()>5?a.length()-5:0):ia+1);
+ String bb = b.substring(ib==-1?(b.length()>5?b.length()-5:0):ib+1);
+ return aa.equalsIgnoreCase(bb);
+ }
+
+ public static boolean soonMatch (String s1, String s2) {
+ String sl1 = nonDetSubstr(s1.toLowerCase());
+ String sl2 = nonDetSubstr(s2.toLowerCase());
+ return sl1.equals(sl2);
+ }
+
+ public static String nonDetSubstr (String s) {
+ if(s.startsWith("the ")) return s.substring(4);
+ if(s.startsWith("a ")) return s.substring(2);
+ if(s.startsWith("this ")) return s.substring(5);
+ if(s.startsWith("that ")) return s.substring(5);
+ if(s.startsWith("these ")) return s.substring(6);
+ if(s.startsWith("those ")) return s.substring(6);
+ return s;
+ }
+
+ public static boolean wordOverlap(Set<String> t1, Set<String> t2) {
+ for (String s : t2){
+ if (t1.contains(s)){
+ return true;
+ }
+ }
+ return false;
+ }
+
+ public static boolean wordSubstring(Set<String> t1, Set<String> t2){
+ for(String s1 : t1){
+ for(String s2 : t2){
+ if(s1.contains(s2) || s2.contains(s1)) return true;
+ }
+ }
+ return false;
+ }
+
+ public static Set<String> contentWords(Annotation a1){
+ Set<String> words = new HashSet<>();
+ for(BaseToken tok : JCasUtil.selectCovered(BaseToken.class, a1)){
+ words.add(tok.getCoveredText().toLowerCase());
+ }
+ return words;
+ }
+
+ public static boolean isPronoun(IdentifiedAnnotation a1){
+ List<BaseToken> tokens = JCasUtil.selectCovered(BaseToken.class, a1);
+
+ if(tokens.size() != 1){
+ return false;
+ }
+
+ BaseToken token = tokens.get(0);
+ if(token.getPartOfSpeech() == null){
+ return false;
+ }
+ if(token.getPartOfSpeech().startsWith("PRP")) return true;
+ if(token.getPartOfSpeech().equals("DT")) return true;
+
+
+ return false;
+ }
+
+ public static boolean inQuote(JCas jcas, Annotation a){
+ boolean inQuote = false;
+ String docText = jcas.getDocumentText();
+
+ // Logic: Find the newline preceding this mention, if there is a quote in between
+ // the start of the line and the start of the mention then the mention is inside quotes.
+ // not foolproof but probably pretty accurate.
+ int lastNewline = docText.lastIndexOf("\n", a.getBegin());
+ if(lastNewline != 0){
+ int firstQuote = docText.indexOf('"', lastNewline);
+ if(firstQuote != 0){
+ inQuote = true;
+ }
+ }
+
+ return inQuote;
+ }
+}
Added: ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/TemporalFeatureExtractor.java
URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/TemporalFeatureExtractor.java?rev=1748736&view=auto
==============================================================================
--- ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/TemporalFeatureExtractor.java (added)
+++ ctakes/trunk/ctakes-coreference/src/main/java/org/apache/ctakes/coreference/ae/features/TemporalFeatureExtractor.java Thu Jun 16 14:51:51 2016
@@ -0,0 +1,54 @@
+package org.apache.ctakes.coreference.ae.features;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.ctakes.dependency.parser.util.DependencyUtility;
+import org.apache.ctakes.relationextractor.ae.features.RelationFeaturesExtractor;
+import org.apache.ctakes.typesystem.type.syntax.ConllDependencyNode;
+import org.apache.ctakes.typesystem.type.textsem.EventMention;
+import org.apache.ctakes.typesystem.type.textsem.IdentifiedAnnotation;
+import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
+import org.apache.uima.fit.util.JCasUtil;
+import org.apache.uima.jcas.JCas;
+import org.cleartk.ml.Feature;
+
+public class TemporalFeatureExtractor implements RelationFeaturesExtractor<IdentifiedAnnotation,IdentifiedAnnotation> {
+
+ public List<Feature> extract(JCas jCas, IdentifiedAnnotation arg1,
+ IdentifiedAnnotation arg2) throws AnalysisEngineProcessException {
+ List<Feature> feats = new ArrayList<>();
+
+ String a1dtr = getDocTimeRelForArg(jCas, arg1);
+ String a2dtr = getDocTimeRelForArg(jCas, arg2);
+
+ feats.add(new Feature("Arg1DTR_" + a1dtr, true));
+ feats.add(new Feature("Arg2DTR_" + a2dtr, true));
+
+ if(a1dtr.equals(a2dtr)){
+ if(!a1dtr.equals("NA")){
+ feats.add(new Feature("DTR_Match", true));
+ }
+ }
+
+ return feats;
+ }
+
+ private static String getDocTimeRelForArg(JCas jCas, IdentifiedAnnotation arg){
+ String dtr = "NA";
+
+ // find EventMentions and grab their event properties
+ ConllDependencyNode node = DependencyUtility.getNominalHeadNode(jCas, arg);
+ if(node != null){
+ List<EventMention> events = JCasUtil.selectCovered(jCas, EventMention.class, node);
+ for(EventMention event : events){
+ if(event.getClass().getSimpleName().equals("EventMention")){
+ if(event.getEvent() != null && event.getEvent().getProperties() != null && event.getEvent().getProperties().getDocTimeRel() != null){
+ dtr = event.getEvent().getProperties().getDocTimeRel();
+ }
+ }
+ }
+ }
+ return dtr;
+ }
+}
\ No newline at end of file