private IList <string> Identifiers(ICounter <string> features, Dictionaries.MentionType mentionType)
{
IList <string> identifiers = new List <string>();
if (mentionType == Dictionaries.MentionType.Pronominal)
{
foreach (string feature in features.KeySet())
{
if (feature.StartsWith("head-word="))
{
identifiers.Add(feature.Replace("head-word=", string.Empty));
return(identifiers);
}
}
}
else
{
if (neTypeConjuntion && mentionType == Dictionaries.MentionType.Proper)
{
foreach (string feature in features.KeySet())
{
if (feature.StartsWith("head-ne-type="))
{
identifiers.Add(mentionType.ToString() + "_" + feature.Replace("head-ne-type=", string.Empty));
return(identifiers);
}
}
}
}
identifiers.Add(mentionType.ToString());
return(identifiers);
}
public Example(Edu.Stanford.Nlp.Coref.Statistical.Example pair, bool isPositive)
{
this.docId = pair.docId;
this.label = isPositive ? 1 : 0;
this.pairwiseFeatures = null;
this.mentionId1 = -1;
this.mentionId2 = pair.mentionId2;
this.mentionType1 = null;
this.mentionType2 = pair.mentionType2;
}
public Example(int docId, Mention m1, Mention m2, double label, CompressedFeatureVector pairwiseFeatures)
{
this.docId = docId;
this.label = label;
this.pairwiseFeatures = pairwiseFeatures;
this.mentionId1 = m1.mentionID;
this.mentionId2 = m2.mentionID;
this.mentionType1 = m1.mentionType;
this.mentionType2 = m2.mentionType;
}
public virtual void RunCoref(Document document)
{
Compressor <string> compressor = new Compressor <string>();
if (Thread.Interrupted())
{
// Allow interrupting
throw new RuntimeInterruptedException();
}
IDictionary <Pair <int, int>, bool> pairs = new Dictionary <Pair <int, int>, bool>();
foreach (KeyValuePair <int, IList <int> > e in CorefUtils.HeuristicFilter(CorefUtils.GetSortedMentions(document), maxMentionDistance, maxMentionDistanceWithStringMatch))
{
foreach (int m1 in e.Value)
{
pairs[new Pair <int, int>(m1, e.Key)] = true;
}
}
DocumentExamples examples = extractor.Extract(0, document, pairs, compressor);
ICounter <Pair <int, int> > pairwiseScores = new ClassicCounter <Pair <int, int> >();
foreach (Example mentionPair in examples.examples)
{
if (Thread.Interrupted())
{
// Allow interrupting
throw new RuntimeInterruptedException();
}
pairwiseScores.IncrementCount(new Pair <int, int>(mentionPair.mentionId1, mentionPair.mentionId2), classifier.Predict(mentionPair, examples.mentionFeatures, compressor));
}
IList <Pair <int, int> > mentionPairs = new List <Pair <int, int> >(pairwiseScores.KeySet());
mentionPairs.Sort(null);
ICollection <int> seenAnaphors = new HashSet <int>();
foreach (Pair <int, int> pair in mentionPairs)
{
if (seenAnaphors.Contains(pair.second))
{
continue;
}
if (Thread.Interrupted())
{
// Allow interrupting
throw new RuntimeInterruptedException();
}
seenAnaphors.Add(pair.second);
Dictionaries.MentionType mt1 = document.predictedMentionsByID[pair.first].mentionType;
Dictionaries.MentionType mt2 = document.predictedMentionsByID[pair.second].mentionType;
if (pairwiseScores.GetCount(pair) > thresholds[new Pair <bool, bool>(mt1 == Dictionaries.MentionType.Pronominal, mt2 == Dictionaries.MentionType.Pronominal)])
{
CorefUtils.MergeCoreferenceClusters(pair, document);
}
}
}
/// <summary>Loads the CorefChain objects from the serialized buffer.</summary>
/// <param name="reader">the buffer</param>
/// <returns>A map from cluster id to clusters</returns>
/// <exception cref="System.IO.IOException"/>
private static IDictionary <int, CorefChain> LoadCorefChains(BufferedReader reader)
{
string line = reader.ReadLine().Trim();
if (line.IsEmpty())
{
return(null);
}
int clusterCount = System.Convert.ToInt32(line);
IDictionary <int, CorefChain> chains = Generics.NewHashMap();
// read each cluster
for (int c = 0; c < clusterCount; c++)
{
line = reader.ReadLine().Trim();
string[] bits = line.Split("\\s");
int cid = System.Convert.ToInt32(bits[0]);
int mentionCount = System.Convert.ToInt32(bits[1]);
IDictionary <IntPair, ICollection <CorefChain.CorefMention> > mentionMap = Generics.NewHashMap();
CorefChain.CorefMention representative = null;
// read each mention in this cluster
for (int m = 0; m < mentionCount; m++)
{
line = reader.ReadLine();
bits = line.Split("\\s");
IntPair key = new IntPair(System.Convert.ToInt32(bits[0]), System.Convert.ToInt32(bits[1]));
bool rep = bits[2].Equals("1");
Dictionaries.MentionType mentionType = ParseMentionType(bits[3]);
Dictionaries.Number number = ParseNumber(bits[4]);
Dictionaries.Gender gender = ParseGender(bits[5]);
Dictionaries.Animacy animacy = ParseAnimacy(bits[6]);
int startIndex = System.Convert.ToInt32(bits[7]);
int endIndex = System.Convert.ToInt32(bits[8]);
int headIndex = System.Convert.ToInt32(bits[9]);
int clusterID = System.Convert.ToInt32(bits[10]);
int mentionID = System.Convert.ToInt32(bits[11]);
int sentNum = System.Convert.ToInt32(bits[12]);
int posLen = System.Convert.ToInt32(bits[13]);
int[] posElems = new int[posLen];
for (int i = 0; i < posLen; i++)
{
posElems[i] = System.Convert.ToInt32(bits[14 + i]);
}
IntTuple position = new IntTuple(posElems);
string span = UnescapeSpace(bits[14 + posLen]);
CorefChain.CorefMention mention = new CorefChain.CorefMention(mentionType, number, gender, animacy, startIndex, endIndex, headIndex, clusterID, mentionID, sentNum, position, span);
ICollection <CorefChain.CorefMention> mentionsWithThisHead = mentionMap[key];
if (mentionsWithThisHead == null)
{
mentionsWithThisHead = Generics.NewHashSet();
mentionMap[key] = mentionsWithThisHead;
}
mentionsWithThisHead.Add(mention);
if (rep)
{
representative = mention;
}
}
// construct the cluster
CorefChain chain = new CorefChain(cid, mentionMap, representative);
chains[cid] = chain;
}
reader.ReadLine();
return(chains);
}
