public static <K1, K2> TwoDimensionalSet<K1, K2> hashSet() { return new TwoDimensionalSet<>(TwoDimensionalMap.<K1, K2, Boolean>hashMap()); }
public Document() { positions = Generics.newHashMap(); mentionheadPositions = Generics.newHashMap(); roleSet = Generics.newHashSet(); corefClusters = Generics.newHashMap(); goldCorefClusters = null; allPredictedMentions = Generics.newHashMap(); allGoldMentions = Generics.newHashMap(); speakers = Generics.newHashMap(); speakerPairs = Generics.newHashSet(); incompatibles = TwoDimensionalSet.hashSet(); incompatibleClusters = TwoDimensionalSet.hashSet(); acronymCache = TwoDimensionalMap.hashMap(); }
max = in.getIndex() > max ? in.getIndex() : max; TwoDimensionalMap<Integer, Integer, IndexedWord> nodes = TwoDimensionalMap.hashMap(); for(CoreNLPProtos.DependencyGraph.Node in: proto.getNodeList()){ CoreLabel token;
TwoDimensionalMap<Integer, Integer, IndexedWord> nodeMap = TwoDimensionalMap.hashMap(); for (IntermediateNode in: nodes){ CoreLabel token = sentence.get(in.index - 1); // index starts at 1!
public static <K1, K2> TwoDimensionalSet<K1, K2> hashSet() { return new TwoDimensionalSet<>(TwoDimensionalMap.<K1, K2, Boolean>hashMap()); }
public static <K1, K2> TwoDimensionalSet<K1, K2> hashSet() { return new TwoDimensionalSet<>(TwoDimensionalMap.<K1, K2, Boolean>hashMap()); }
public static <K1, K2> TwoDimensionalSet<K1, K2> hashSet() { return new TwoDimensionalSet<K1, K2>(TwoDimensionalMap.<K1, K2, Boolean>hashMap()); }
public Document() { positions = Generics.newHashMap(); mentionheadPositions = Generics.newHashMap(); roleSet = Generics.newHashSet(); corefClusters = Generics.newHashMap(); goldCorefClusters = null; allPredictedMentions = Generics.newHashMap(); allGoldMentions = Generics.newHashMap(); speakers = Generics.newHashMap(); speakerPairs = Generics.newHashSet(); incompatibles = TwoDimensionalSet.hashSet(); incompatibleClusters = TwoDimensionalSet.hashSet(); acronymCache = TwoDimensionalMap.hashMap(); }
public Document() { positions = Generics.newHashMap(); mentionheadPositions = Generics.newHashMap(); roleSet = Generics.newHashSet(); corefClusters = Generics.newHashMap(); goldCorefClusters = null; allPredictedMentions = Generics.newHashMap(); allGoldMentions = Generics.newHashMap(); speakers = Generics.newHashMap(); speakerPairs = Generics.newHashSet(); incompatibles = TwoDimensionalSet.hashSet(); incompatibleClusters = TwoDimensionalSet.hashSet(); acronymCache = TwoDimensionalMap.hashMap(); }
max = in.getIndex() > max ? in.getIndex() : max; TwoDimensionalMap<Integer, Integer, IndexedWord> nodes = TwoDimensionalMap.hashMap(); for(CoreNLPProtos.DependencyGraph.Node in: proto.getNodeList()){ CoreLabel token;
TwoDimensionalMap<Integer, Integer, IndexedWord> nodeMap = TwoDimensionalMap.hashMap(); for (IntermediateNode in: nodes){ CoreLabel token = sentence.get(in.index - 1); // index starts at 1!