/// <summary>
/// Copy constructor.
/// </summary>
/// <param name="other">The ArrayCoreMap to copy. It may not be null.</param>
public ArrayCoreMap(ICoreMap other)
{
/*Set<Class<?>>*/
var otherKeys = other.KeySet();
psize = otherKeys.Count;
keys = new Type[psize];
values = new Object[psize];
int i = 0;
foreach (var key in otherKeys)
{
this.keys[i] = key;
this.values[i] = other.Get(key);
i++;
}
}
public virtual void TestKbpSpanishWorks()
{
Properties props = PropertiesUtils.AsProperties("annotators", "tokenize, cleanxml, ssplit", "tokenize.language", "es", "tokenize.options", "tokenizeNLs,ptb3Escaping=true", "ssplit.newlineIsSentenceBreak", "two", "ssplit.tokenPatternsToDiscard"
, "\\n,\\*NL\\*", "ssplit.boundaryMultiTokenRegex", "/\\*NL\\*/ /\\p{Lu}[-\\p{L}]+/+ /,/ ( /[-\\p{L}]+/+ /,/ )? " + "/[1-3]?[0-9]/ /\\p{Ll}{3,5}/ /=LRB=/ /\\p{Lu}\\p{L}+/ /=RRB=/ /--/", "clean.xmltags", "headline|text|post", "clean.singlesentencetags"
, "HEADLINE|AUTHOR", "clean.sentenceendingtags", "TEXT|POST|QUOTE", "clean.turntags", "POST|QUOTE", "clean.speakertags", "AUTHOR", "clean.datetags", "DATE_TIME", "clean.doctypetags", "DOC", "clean.docAnnotations", "docID=doc[id]", "clean.sectiontags"
, "HEADLINE|POST", "clean.sectionAnnotations", "sectionID=post[id],sectionDate=post[datetime],author=post[author]", "clean.quotetags", "quote", "clean.quoteauthorattributes", "orig_author", "clean.tokenAnnotations", "link=a[href],speaker=post[author],speaker=quote[orig_author]"
);
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
Annotation document1 = new Annotation(kbpSpanishDocument);
pipeline.Annotate(document1);
IList <ICoreMap> sentences = document1.Get(typeof(CoreAnnotations.SentencesAnnotation));
for (int i = 0; i < Math.Min(kbpSpanishSentences.Length, sentences.Count); i++)
{
ICoreMap sentence = sentences[i];
string sentenceText = SentenceUtils.ListToString(sentence.Get(typeof(CoreAnnotations.TokensAnnotation)));
NUnit.Framework.Assert.AreEqual(kbpSpanishSentences[i], sentenceText, "Bad sentence #" + i);
}
NUnit.Framework.Assert.AreEqual(kbpSpanishSentences.Length, sentences.Count, "Bad total number of sentences");
}
public virtual Person DoCoreference(int corefMapKey, ICoreMap quote)
{
if (pronounCorefMap == null)
{
return(null);
}
ICollection <Person> quoteNames = new HashSet <Person>();
if (quote != null)
{
quoteNames = GetNamesInParagraph(quote);
}
string referent = pronounCorefMap[corefMapKey];
Person candidate = ResolveAmbiguities(referent);
if (candidate != null && !quoteNames.Contains(candidate))
{
return(candidate);
}
return(null);
}
public virtual void Process(long id, Annotation doc)
{
ICoreMap sentence = doc.Get(typeof(CoreAnnotations.SentencesAnnotation))[0];
SemanticGraph depparse = sentence.Get(typeof(SemanticGraphCoreAnnotations.BasicDependenciesAnnotation));
log.Info("| " + sentence.Get(typeof(CoreAnnotations.TextAnnotation)));
// Get all valid subject spans
BitSet consumedAsSubjects = new BitSet();
IList <Span> subjectSpans = new List <Span>();
foreach (IndexedWord head in depparse.TopologicalSort())
{
// Check if the node is a noun/pronoun
if (head.Tag().StartsWith("N") || head.Tag().Equals("PRP"))
{
// Try to get the NP chunk
Optional <IList <IndexedWord> > subjectChunk = segmenter.GetValidChunk(depparse, head, segmenter.ValidSubjectArcs, Optional.Empty(), true);
if (subjectChunk.IsPresent())
{
// Make sure it's not already a member of a larger NP
foreach (IndexedWord tok in subjectChunk.Get())
{
if (consumedAsSubjects.Get(tok.Index()))
{
goto NEXTNODE_continue;
}
}
// Already considered. Continue to the next node.
// Register it as an NP
foreach (IndexedWord tok_1 in subjectChunk.Get())
{
consumedAsSubjects.Set(tok_1.Index());
}
// Add it as a subject
subjectSpans.Add(ToSpan(subjectChunk.Get()));
}
}
}
NEXTNODE_break :;
}
/// <summary>
/// Converts NamedEntityTagAnnotation tags into
/// <see cref="Edu.Stanford.Nlp.IE.Machinereading.Structure.EntityMention"/>
/// s. This
/// finds the longest sequence of NamedEntityTagAnnotation tags of the matching
/// type.
/// </summary>
/// <param name="sentence">A sentence annotated with NamedEntityTagAnnotation</param>
public virtual void MakeAnnotationFromAllNERTags(ICoreMap sentence)
{
IList <CoreLabel> words = sentence.Get(typeof(CoreAnnotations.TokensAnnotation));
IList <EntityMention> mentions = sentence.Get(typeof(MachineReadingAnnotations.EntityMentionsAnnotation));
System.Diagnostics.Debug.Assert(words != null);
if (mentions == null)
{
this.logger.Info("mentions are null");
mentions = new List <EntityMention>();
}
for (int start = 0; start < words.Count; start++)
{
int end;
// find the first token after start that isn't of nerType
string lastneTag = null;
string ne = null;
for (end = start; end < words.Count; end++)
{
ne = words[end].Get(typeof(CoreAnnotations.NamedEntityTagAnnotation));
if (ne.Equals(SeqClassifierFlags.DefaultBackgroundSymbol) || (lastneTag != null && !ne.Equals(lastneTag)))
{
break;
}
lastneTag = ne;
}
if (end > start)
{
// found a match!
string entityType = this.GetEntityTypeForTag(lastneTag);
EntityMention m = entityMentionFactory.ConstructEntityMention(EntityMention.MakeUniqueId(), sentence, new Span(start, end), new Span(start, end), entityType, null, null);
//TODO: changed entityType in the above sentence to nerTag - Sonal
logger.Info("Created " + entityType + " entity mention: " + m);
start = end - 1;
mentions.Add(m);
}
}
sentence.Set(typeof(MachineReadingAnnotations.EntityMentionsAnnotation), mentions);
}
public virtual void AnnotateSentence(ICoreMap sentence)
{
// this stores all relation mentions generated by this extractor
IList <RelationMention> relations = new List <RelationMention>();
// extractAllRelations creates new objects for every predicted relation
foreach (RelationMention rel in ExtractAllRelations(sentence))
{
// add all relations. potentially useful for a joint model
// if (! RelationMention.isUnrelatedLabel(rel.getType()))
relations.Add(rel);
}
// caution: this removes the old list of relation mentions!
foreach (RelationMention r in relations)
{
if (!r.GetType().Equals(RelationMention.Unrelated))
{
logger.Fine("Found positive relation in annotateSentence: " + r);
}
}
sentence.Set(typeof(MachineReadingAnnotations.RelationMentionsAnnotation), relations);
}
public virtual void Annotate(Annotation annotation)
{
// extract entities and relations
Annotation output = mr.Annotate(annotation);
// transfer entities/relations back to the original annotation
IList <ICoreMap> outputSentences = output.Get(typeof(CoreAnnotations.SentencesAnnotation));
IList <ICoreMap> origSentences = annotation.Get(typeof(CoreAnnotations.SentencesAnnotation));
for (int i = 0; i < outputSentences.Count; i++)
{
ICoreMap outSent = outputSentences[i];
ICoreMap origSent = origSentences[i];
// set entities
IList <EntityMention> entities = outSent.Get(typeof(MachineReadingAnnotations.EntityMentionsAnnotation));
origSent.Set(typeof(MachineReadingAnnotations.EntityMentionsAnnotation), entities);
if (verbose && entities != null)
{
log.Info("Extracted the following entities:");
foreach (EntityMention e in entities)
{
log.Info("\t" + e);
}
}
// set relations
IList <RelationMention> relations = outSent.Get(typeof(MachineReadingAnnotations.RelationMentionsAnnotation));
origSent.Set(typeof(MachineReadingAnnotations.RelationMentionsAnnotation), relations);
if (verbose && relations != null)
{
log.Info("Extracted the following relations:");
foreach (RelationMention r in relations)
{
if (!r.GetType().Equals(RelationMention.Unrelated))
{
log.Info(r);
}
}
}
}
}
private void CountAdjacentMentions(ICoreMap sent)
{
IList <EntityMention> mentions = sent.Get(typeof(MachineReadingAnnotations.EntityMentionsAnnotation));
if (mentions != null)
{
foreach (EntityMention m1 in mentions)
{
foreach (EntityMention m2 in mentions)
{
if (m1 == m2)
{
continue;
}
if (m1.GetHeadTokenEnd() == m2.GetHeadTokenStart() && m1.GetType().Equals(m2.GetType()))
{
adjacentEntityMentions.IncrementCount(m1.GetType());
}
}
}
}
}
/// <exception cref="System.IO.IOException"/>
public virtual void Annotate(ICoreMap document)
{
try
{
//--Create Input File
//(create file)
File inputFile = File.CreateTempFile("heideltime", ".input");
//(write to file)
PrintWriter inputWriter = new PrintWriter(inputFile);
PrepareHeidelTimeInput(inputWriter, document);
inputWriter.Close();
Optional <string> pubDate = GetPubDate(document);
//--Build Command
IList <string> args = new List <string>(Arrays.AsList("java", "-jar", this.heideltimePath.GetPath() + "/heideltime.jar", "-c", this.heideltimePath.GetPath() + "/config.props", "-l", this.language, "-t", "NEWS"));
if (pubDate.IsPresent())
{
args.Add("-dct");
args.Add(pubDate.Get());
}
args.Add(inputFile.GetPath());
// run HeidelTime on the input file
ProcessBuilder process = new ProcessBuilder(args);
StringWriter outputWriter = new StringWriter();
SystemUtils.Run(process, outputWriter, null);
string output = outputWriter.GetBuffer().ToString();
IList <ICoreMap> timexAnns = outputReader.Process(document, output);
document.Set(typeof(TimeAnnotations.TimexAnnotations), timexAnns);
if (outputResults)
{
System.Console.Out.WriteLine(timexAnns);
}
}
catch (Exception e)
{
Sharpen.Runtime.PrintStackTrace(e, System.Console.Error);
System.Console.Error.WriteLine("error running HeidelTime on this doc: " + document.Get(typeof(CoreAnnotations.DocIDAnnotation)));
}
}
/// <summary>Print a description of this triple, formatted like the ReVerb outputs.</summary>
public virtual string ToReverbString(string docid, ICoreMap sentence)
{
int sentIndex = -1;
int subjIndex = -1;
int relationIndex = -1;
int objIndex = -1;
int subjIndexEnd = -1;
int relationIndexEnd = -1;
int objIndexEnd = -1;
if (!relation.IsEmpty())
{
sentIndex = relation[0].SentIndex();
relationIndex = relation[0].Index() - 1;
relationIndexEnd = relation[relation.Count - 1].Index();
}
if (!subject.IsEmpty())
{
if (sentIndex < 0)
{
sentIndex = subject[0].SentIndex();
}
subjIndex = subject[0].Index() - 1;
subjIndexEnd = subject[subject.Count - 1].Index();
}
if ([email protected]())
{
if (sentIndex < 0)
{
sentIndex = subject[0].SentIndex();
}
objIndex = @object[0].Index() - 1;
objIndexEnd = @object[@object.Count - 1].Index();
}
return((docid == null ? "no_doc_id" : docid) + '\t' + sentIndex + '\t' + SubjectGloss().Replace('\t', ' ') + '\t' + RelationGloss().Replace('\t', ' ') + '\t' + ObjectGloss().Replace('\t', ' ') + '\t' + subjIndex + '\t' + subjIndexEnd + '\t'
+ relationIndex + '\t' + relationIndexEnd + '\t' + objIndex + '\t' + objIndexEnd + '\t' + ConfidenceGloss() + '\t' + StringUtils.Join(sentence.Get(typeof(CoreAnnotations.TokensAnnotation)).Stream().Map(null), " ") + '\t' + StringUtils.Join(
sentence.Get(typeof(CoreAnnotations.TokensAnnotation)).Stream().Map(null), " ") + '\t' + SubjectLemmaGloss().Replace('\t', ' ') + '\t' + RelationLemmaGloss().Replace('\t', ' ') + '\t' + ObjectLemmaGloss().Replace('\t', ' '));
}
protected internal static void ExtractPremarkedEntityMentions(ICoreMap s, IList <Mention> mentions, ICollection <IntPair> mentionSpanSet, ICollection <IntPair> namedEntitySpanSet)
{
IList <CoreLabel> sent = s.Get(typeof(CoreAnnotations.TokensAnnotation));
SemanticGraph dependency = s.Get(typeof(SemanticGraphCoreAnnotations.EnhancedDependenciesAnnotation));
int beginIndex = -1;
foreach (CoreLabel w in sent)
{
MultiTokenTag t = w.Get(typeof(CoreAnnotations.MentionTokenAnnotation));
if (t != null)
{
// Part of a mention
if (t.IsStart())
{
// Start of mention
beginIndex = w.Get(typeof(CoreAnnotations.IndexAnnotation)) - 1;
}
if (t.IsEnd())
{
// end of mention
int endIndex = w.Get(typeof(CoreAnnotations.IndexAnnotation));
if (beginIndex >= 0)
{
IntPair mSpan = new IntPair(beginIndex, endIndex);
int dummyMentionId = -1;
Mention m = new Mention(dummyMentionId, beginIndex, endIndex, dependency, new List <CoreLabel>(sent.SubList(beginIndex, endIndex)));
mentions.Add(m);
mentionSpanSet.Add(mSpan);
beginIndex = -1;
}
else
{
SieveCoreferenceSystem.logger.Warning("Start of marked mention not found in sentence: " + t + " at tokenIndex=" + (w.Get(typeof(CoreAnnotations.IndexAnnotation)) - 1) + " for " + s.Get(typeof(CoreAnnotations.TextAnnotation)));
}
}
}
}
}
protected internal virtual void RemoveSpuriousMentionsEn(Annotation doc, IList <IList <Mention> > predictedMentions, Dictionaries dict)
{
IList <ICoreMap> sentences = doc.Get(typeof(CoreAnnotations.SentencesAnnotation));
for (int i = 0; i < predictedMentions.Count; i++)
{
ICoreMap s = sentences[i];
IList <Mention> mentions = predictedMentions[i];
IList <CoreLabel> sent = s.Get(typeof(CoreAnnotations.TokensAnnotation));
ICollection <Mention> remove = Generics.NewHashSet();
foreach (Mention m in mentions)
{
string headPOS = m.headWord.Get(typeof(CoreAnnotations.PartOfSpeechAnnotation));
// non word such as 'hmm'
if (dict.nonWords.Contains(m.headString))
{
remove.Add(m);
}
// adjective form of nations
// the [American] policy -> not mention
// speak in [Japanese] -> mention
// check if the mention is noun and the next word is not noun
if (dict.IsAdjectivalDemonym(m.SpanToString()))
{
if (!headPOS.StartsWith("N") || (m.endIndex < sent.Count && sent[m.endIndex].Tag().StartsWith("N")))
{
remove.Add(m);
}
}
// stop list (e.g., U.S., there)
if (InStopList(m))
{
remove.Add(m);
}
}
mentions.RemoveAll(remove);
}
}
public virtual bool Matches(ICoreMap o1, ICoreMap o2)
{
foreach (Type key in keys)
{
object v1 = o1.Get(key);
object v2 = o2.Get(key);
if (v1 != null)
{
if (!v1.Equals(v2))
{
return(false);
}
}
else
{
if (v2 != null)
{
return(false);
}
}
}
return(true);
}
public virtual int DetermineRelFlags(ICoreMap annotation, TimeExpression te)
{
int flags = 0;
bool flagsSet = false;
if (te.value.GetTags() != null)
{
IValue v = te.value.GetTags().GetTag("resolveTo");
if (v != null && v.Get() is Number)
{
flags = ((Number)v.Get());
flagsSet = true;
}
}
if (!flagsSet)
{
if (te.GetTemporal() is SUTime.PartialTime)
{
flags = SUTime.ResolveToClosest;
}
}
return(flags);
}
// temporary for debug
protected internal static void AddGoldMentions(IList <ICoreMap> sentences, IList <ICollection <IntPair> > mentionSpanSetList, IList <IList <Mention> > predictedMentions, IList <IList <Mention> > allGoldMentions)
{
for (int i = 0; i < sz; i++)
{
IList <Mention> mentions = predictedMentions[i];
ICoreMap sent = sentences[i];
IList <CoreLabel> tokens = sent.Get(typeof(CoreAnnotations.TokensAnnotation));
ICollection <IntPair> mentionSpanSet = mentionSpanSetList[i];
IList <Mention> golds = allGoldMentions[i];
foreach (Mention g in golds)
{
IntPair pair = new IntPair(g.startIndex, g.endIndex);
if (!mentionSpanSet.Contains(pair))
{
int dummyMentionId = -1;
Mention m = new Mention(dummyMentionId, g.startIndex, g.endIndex, tokens, sent.Get(typeof(SemanticGraphCoreAnnotations.BasicDependenciesAnnotation)), sent.Get(typeof(SemanticGraphCoreAnnotations.EnhancedDependenciesAnnotation)) != null ? sent
.Get(typeof(SemanticGraphCoreAnnotations.EnhancedDependenciesAnnotation)) : sent.Get(typeof(SemanticGraphCoreAnnotations.BasicDependenciesAnnotation)), new List <CoreLabel>(tokens.SubList(g.startIndex, g.endIndex)));
mentions.Add(m);
mentionSpanSet.Add(pair);
}
}
}
}
private void RecognizeNumberSequences(IList <CoreLabel> words, ICoreMap document, ICoreMap sentence)
{
// we need to copy here because NumberSequenceClassifier overwrites the AnswerAnnotation
IList <CoreLabel> newWords = NumberSequenceClassifier.CopyTokens(words, sentence);
nsc.ClassifyWithGlobalInformation(newWords, document, sentence);
// copy AnswerAnnotation back. Do not overwrite!
// also, copy all the additional annotations generated by SUTime and NumberNormalizer
for (int i = 0; i < sz; i++)
{
CoreLabel origWord = words[i];
CoreLabel newWord = newWords[i];
// log.info(newWord.word() + " => " + newWord.get(CoreAnnotations.AnswerAnnotation.class) + " " + origWord.ner());
string before = origWord.Get(typeof(CoreAnnotations.AnswerAnnotation));
string newGuess = newWord.Get(typeof(CoreAnnotations.AnswerAnnotation));
if ((before == null || before.Equals(nsc.flags.backgroundSymbol) || before.Equals("MISC")) && !newGuess.Equals(nsc.flags.backgroundSymbol))
{
origWord.Set(typeof(CoreAnnotations.AnswerAnnotation), newGuess);
}
// transfer other annotations generated by SUTime or NumberNormalizer
NumberSequenceClassifier.TransferAnnotations(newWord, origWord);
}
}
/// <summary>Parse a string with SUTime.</summary>
/// <exception cref="SUTimeParsingError">if anything goes wrong</exception>
/// <exception cref="Edu.Stanford.Nlp.Time.SUTimeSimpleParser.SUTimeParsingError"/>
public static SUTime.Temporal Parse(string str)
{
try
{
Annotation doc = new Annotation(str);
pipeline.Annotate(doc);
System.Diagnostics.Debug.Assert(doc.Get(typeof(CoreAnnotations.SentencesAnnotation)) != null);
System.Diagnostics.Debug.Assert(!doc.Get(typeof(CoreAnnotations.SentencesAnnotation)).IsEmpty());
IList <ICoreMap> timexAnnotations = doc.Get(typeof(TimeAnnotations.TimexAnnotations));
if (timexAnnotations.Count > 1)
{
throw new Exception("Too many timexes for '" + str + '\'');
}
ICoreMap timex = timexAnnotations[0];
return(timex.Get(typeof(TimeExpression.Annotation)).GetTemporal());
}
catch (Exception e)
{
SUTimeSimpleParser.SUTimeParsingError parsingError = new SUTimeSimpleParser.SUTimeParsingError(str);
parsingError.InitCause(e);
throw parsingError;
}
}
protected internal virtual void FindHead(ICoreMap s, IList <Mention> mentions)
{
Tree tree = s.Get(typeof(TreeCoreAnnotations.TreeAnnotation));
IList <CoreLabel> sent = s.Get(typeof(CoreAnnotations.TokensAnnotation));
tree.IndexSpans(0);
foreach (Mention m in mentions)
{
Tree head = FindSyntacticHead(m, tree, sent);
m.headIndex = ((CoreLabel)head.Label()).Get(typeof(CoreAnnotations.IndexAnnotation)) - 1;
m.headWord = sent[m.headIndex];
m.headString = m.headWord.Get(typeof(CoreAnnotations.TextAnnotation)).ToLower(Locale.English);
int start = m.headIndex - m.startIndex;
if (start < 0 || start >= m.originalSpan.Count)
{
SieveCoreferenceSystem.logger.Warning("Invalid index for head " + start + "=" + m.headIndex + "-" + m.startIndex + ": originalSpan=[" + StringUtils.JoinWords(m.originalSpan, " ") + "], head=" + m.headWord);
SieveCoreferenceSystem.logger.Warning("Setting head string to entire mention");
m.headIndex = m.startIndex;
m.headWord = m.originalSpan.Count > 0 ? m.originalSpan[0] : sent[m.startIndex];
m.headString = m.originalSpan.ToString();
}
}
}
/// <exception cref="System.IO.IOException"/>
private static void RecallErrors(IList<IList<Mention>> goldMentions, IList<IList<Mention>> predictedMentions, Annotation doc)
{
IList<ICoreMap> coreMaps = doc.Get(typeof(CoreAnnotations.SentencesAnnotation));
int numSentences = goldMentions.Count;
for (int i = 0; i < numSentences; i++)
{
ICoreMap coreMap = coreMaps[i];
IList<CoreLabel> words = coreMap.Get(typeof(CoreAnnotations.TokensAnnotation));
Tree tree = coreMap.Get(typeof(TreeCoreAnnotations.TreeAnnotation));
IList<Mention> goldMentionsSent = goldMentions[i];
IList<Pair<int, int>> goldMentionsSpans = ExtractSpans(goldMentionsSent);
foreach (Pair<int, int> mentionSpan in goldMentionsSpans)
{
logger.Finer("RECALL ERROR\n");
logger.Finer(coreMap + "\n");
for (int x = mentionSpan.first; x < mentionSpan.second; x++)
{
logger.Finer(words[x].Value() + " ");
}
logger.Finer("\n" + tree + "\n");
}
}
}
private void AnnotateExpressions(ICoreMap annotation, IList <T> expressions)
{
// TODO: Logging can be excessive
IList <T> toDiscard = new List <T>();
foreach (T te in expressions)
{
// Add attributes and all
if (te.annotation == null)
{
try
{
bool extractOkay = te.ExtractAnnotation(env, annotation);
if (verbose && extractOkay)
{
log.Info("annotateExpressions() matched " + te + " from " + annotation);
}
if (!extractOkay)
{
// Things didn't turn out so well
toDiscard.Add(te);
log.Warn("Error extracting annotation from " + te);
}
}
catch (Exception ex)
{
/*+ ", " + te.getExtractErrorMessage() */
if (verbose)
{
log.Warn("Error extracting annotation from " + te);
log.Warn(ex);
}
}
}
}
expressions.RemoveAll(toDiscard);
}
public static SUTime.Temporal ParseOrNull(string str)
{
Annotation doc = new Annotation(str);
pipeline.Annotate(doc);
if (doc.Get(typeof(CoreAnnotations.SentencesAnnotation)) == null)
{
return(null);
}
if (doc.Get(typeof(CoreAnnotations.SentencesAnnotation)).IsEmpty())
{
return(null);
}
IList <ICoreMap> timexAnnotations = doc.Get(typeof(TimeAnnotations.TimexAnnotations));
if (timexAnnotations.Count > 1)
{
return(null);
}
else
{
if (timexAnnotations.IsEmpty())
{
return(null);
}
}
ICoreMap timex = timexAnnotations[0];
if (timex.Get(typeof(TimeExpression.Annotation)) == null)
{
return(null);
}
else
{
return(timex.Get(typeof(TimeExpression.Annotation)).GetTemporal());
}
}
public static void WriteConllFile(string outFile, IList <ICoreMap> sentences, IList <DependencyTree> trees)
{
try
{
PrintWriter output = IOUtils.GetPrintWriter(outFile);
for (int i = 0; i < sentences.Count; i++)
{
ICoreMap sentence = sentences[i];
DependencyTree tree = trees[i];
IList <CoreLabel> tokens = sentence.Get(typeof(CoreAnnotations.TokensAnnotation));
for (int j = 1; j <= size; ++j)
{
CoreLabel token = tokens[j - 1];
output.Printf("%d\t%s\t_\t%s\t%s\t_\t%d\t%s\t_\t_%n", j, token.Word(), token.Tag(), token.Tag(), tree.GetHead(j), tree.GetLabel(j));
}
output.Println();
}
output.Close();
}
catch (Exception e)
{
throw new RuntimeIOException(e);
}
}
private void CleanupTags(ICoreMap cm, IDictionary <object, bool> cleaned)
{
cm.Remove(typeof(Tags.TagsAnnotation));
foreach (Type key in cm.KeySet())
{
object obj = cm.Get(key);
if (!cleaned.Contains(obj))
{
cleaned[obj] = false;
if (obj is ICoreMap)
{
CleanupTags((ICoreMap)obj, cleaned);
}
else
{
if (obj is ICollection)
{
CleanupTags((ICollection)obj, cleaned);
}
}
cleaned[obj] = true;
}
}
}
/// <exception cref="System.Exception"/>
public virtual Document MakeDocument(InputDoc input)
{
IList <IList <Mention> > mentions = new List <IList <Mention> >();
if (CorefProperties.UseGoldMentions(props))
{
IList <ICoreMap> sentences = input.annotation.Get(typeof(CoreAnnotations.SentencesAnnotation));
for (int i = 0; i < sentences.Count; i++)
{
ICoreMap sentence = sentences[i];
IList <CoreLabel> sentenceWords = sentence.Get(typeof(CoreAnnotations.TokensAnnotation));
IList <Mention> sentenceMentions = new List <Mention>();
mentions.Add(sentenceMentions);
foreach (Mention g in input.goldMentions[i])
{
sentenceMentions.Add(new Mention(-1, g.startIndex, g.endIndex, sentenceWords, null, null, new List <CoreLabel>(sentenceWords.SubList(g.startIndex, g.endIndex))));
}
md.FindHead(sentence, sentenceMentions);
}
}
else
{
foreach (ICoreMap sentence in input.annotation.Get(typeof(CoreAnnotations.SentencesAnnotation)))
{
mentions.Add(sentence.Get(typeof(CorefCoreAnnotations.CorefMentionsAnnotation)));
}
}
Document doc = new Document(input, mentions);
if (input.goldMentions != null)
{
FindGoldMentionHeads(doc);
}
DocumentPreprocessor.Preprocess(doc, dict, null, headFinder);
return(doc);
}
public virtual void TestAlwaysNewlineIsSentenceBreakSettings()
{
string text = "This is \none sentence\n\nThis is not another.";
string[] sents = new string[] { "This is", "one sentence", "This is not another ." };
Properties props = PropertiesUtils.AsProperties("annotators", "tokenize, ssplit", "ssplit.newlineIsSentenceBreak", "always");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
Annotation document1 = new Annotation(text);
pipeline.Annotate(document1);
IList <ICoreMap> sentences = document1.Get(typeof(CoreAnnotations.SentencesAnnotation));
NUnit.Framework.Assert.AreEqual(3, sentences.Count);
// make sure that there are the correct # of tokens (count does contain NL tokens)
IList <CoreLabel> tokens = document1.Get(typeof(CoreAnnotations.TokensAnnotation));
NUnit.Framework.Assert.AreEqual(9, tokens.Count);
for (int i = 0; i < Math.Min(sents.Length, sentences.Count); i++)
{
ICoreMap sentence = sentences[i];
string sentenceText = SentenceUtils.ListToString(sentence.Get(typeof(CoreAnnotations.TokensAnnotation)));
NUnit.Framework.Assert.AreEqual(sents[i], sentenceText, "Bad sentence #" + i);
}
}
// for filling in the text of a mention
public virtual string TokenRangeToString(Pair <int, int> tokenRange)
{
IList <CoreLabel> tokens = doc.Get(typeof(CoreAnnotations.TokensAnnotation));
// see if the token range matches an entity mention
IList <ICoreMap> entityMentionsInDoc = doc.Get(typeof(CoreAnnotations.MentionsAnnotation));
int potentialMatchingEntityMentionIndex = tokens[tokenRange.first].Get(typeof(CoreAnnotations.EntityMentionIndexAnnotation));
ICoreMap potentialMatchingEntityMention = null;
if (entityMentionsInDoc != null && potentialMatchingEntityMentionIndex != null)
{
potentialMatchingEntityMention = entityMentionsInDoc[potentialMatchingEntityMentionIndex];
}
// if there is a matching entity mention, return it's text (which has been processed to remove
// things like newlines and xml)...if there isn't return the full substring of the document text
if (potentialMatchingEntityMention != null && potentialMatchingEntityMention.Get(typeof(CoreAnnotations.CharacterOffsetBeginAnnotation)) == tokens[tokenRange.first].BeginPosition() && potentialMatchingEntityMention.Get(typeof(CoreAnnotations.CharacterOffsetEndAnnotation
)) == tokens[tokenRange.second].EndPosition())
{
return(potentialMatchingEntityMention.Get(typeof(CoreAnnotations.TextAnnotation)));
}
else
{
return(Sharpen.Runtime.Substring(doc.Get(typeof(CoreAnnotations.TextAnnotation)), tokens[tokenRange.first].BeginPosition(), tokens[tokenRange.second].EndPosition()));
}
}
public static void AddEnhancedSentences(Annotation doc)
{
//for every sentence that begins a paragraph: append this sentence and the previous one and see if sentence splitter would make a single sentence out of it. If so, add as extra sentence.
//for each sieve that potentially uses augmentedSentences in original:
IList <ICoreMap> sentences = doc.Get(typeof(CoreAnnotations.SentencesAnnotation));
WordToSentenceProcessor wsp = new WordToSentenceProcessor(WordToSentenceProcessor.NewlineIsSentenceBreak.Never);
//create SentenceSplitter that never splits on newline
int prevParagraph = 0;
for (int i = 1; i < sentences.Count; i++)
{
ICoreMap sentence = sentences[i];
ICoreMap prevSentence = sentences[i - 1];
IList <CoreLabel> tokensConcat = new List <CoreLabel>();
Sharpen.Collections.AddAll(tokensConcat, prevSentence.Get(typeof(CoreAnnotations.TokensAnnotation)));
Sharpen.Collections.AddAll(tokensConcat, sentence.Get(typeof(CoreAnnotations.TokensAnnotation)));
IList <IList <CoreLabel> > sentenceTokens = wsp.Process(tokensConcat);
if (sentenceTokens.Count == 1)
{
//wsp would have put them into a single sentence --> add enhanced sentence.
sentence.Set(typeof(QuoteAttributionUtils.EnhancedSentenceAnnotation), ConstructSentence(sentenceTokens[0], prevSentence, sentence));
}
}
}
public static string TokensAndNELabelsToString(ICoreMap sentence)
{
StringBuilder os = new StringBuilder();
IList <CoreLabel> tokens = sentence.Get(typeof(CoreAnnotations.TokensAnnotation));
if (tokens != null)
{
bool first = true;
foreach (CoreLabel token in tokens)
{
if (!first)
{
os.Append(" ");
}
os.Append(token.Word());
if (token.Ner() != null && !token.Ner().Equals("O"))
{
os.Append("/" + token.Ner());
}
first = false;
}
}
return(os.ToString());
}
/// <summary>Process an entity given the NER tag, extracted modifier and the next word in the document.</summary>
/// <remarks>
/// Process an entity given the NER tag, extracted modifier and the next word in the document.
/// The normalized quantity will be written in place.
/// </remarks>
/// <param name="l">A collector that collects annotations for the entity.</param>
/// <param name="entityType">Quantifiable NER tag.</param>
/// <param name="compModifier">
/// The extracted modifier around the entity of interest. Different NER tags should
/// have different extraction rules.
/// </param>
/// <param name="nextWord">Next word in the document.</param>
/// <param name="document">Reference to the document.</param>
/// <?/>
/// <returns/>
private static IList <E> ProcessEntity <E>(IList <E> l, string entityType, string compModifier, string nextWord, ICoreMap document)
where E : ICoreMap
{
// convert the entity annotations into a string
string s = SingleEntityToString(l);
StringBuilder sb = new StringBuilder();
// convert all full digits to half digits
for (int i = 0; i < sz; i++)
{
string ch = Sharpen.Runtime.Substring(s, i, i + 1);
if (fullDigitToHalfDigit.Contains(ch))
{
ch = fullDigitToHalfDigit[ch];
}
sb.Append(ch);
}
s = sb.ToString();
string p = null;
switch (entityType)
{
case NumberTag:
{
p = string.Empty;
if (compModifier != null)
{
p = compModifier;
}
string q = NormalizedNumberString(s, nextWord, 1.0);
if (q != null)
{
p = p.Concat(q);
}
else
{
p = null;
}
break;
}
case OrdinalTag:
{
// ordinal won't have modifier
p = NormalizedOrdinalString(s, nextWord);
break;
}
case PercentTag:
{
p = NormalizedPercentString(s, nextWord);
break;
}
case MoneyTag:
{
p = string.Empty;
if (compModifier != null)
{
p = compModifier;
}
q = NormalizedMoneyString(s, nextWord);
if (q != null)
{
p = p.Concat(q);
}
else
{
p = null;
}
break;
}
case DateTag:
{
if (s.Matches(BasicYyyymmddPattern) || s.Matches(BasicMmddPattern) || s.Matches(EnglishMmddyyyyPattern) || s.Matches(BasicDdPattern) || s.Matches(RelativeTimePattern) || s.Matches(BirthDecadePattern))
{
string docdate = document.Get(typeof(CoreAnnotations.DocDateAnnotation));
p = NormalizeDateString(s, docdate);
}
break;
}
case TimeTag:
{
break;
}
}
// Write the normalized NER values in place
foreach (E wi in l)
{
if (p != null)
{
wi.Set(typeof(CoreAnnotations.NormalizedNamedEntityTagAnnotation), p);
}
}
// This return value is not necessarily useful as the labelling is done in place.
return(l);
}
// Patterns used by DATE and TIME (must be after the static initializers to make use of the modifiers)
// static methods
/// <summary>
/// Identifies contiguous MONEY, TIME, DATE, or PERCENT entities
/// and tags each of their constituents with a "normalizedQuantity"
/// label which contains the appropriate normalized string corresponding to
/// the full quantity.
/// </summary>
/// <remarks>
/// Identifies contiguous MONEY, TIME, DATE, or PERCENT entities
/// and tags each of their constituents with a "normalizedQuantity"
/// label which contains the appropriate normalized string corresponding to
/// the full quantity.
/// Unlike the English normalizer, this method currently does not support
/// concatenation or SUTime.
/// </remarks>
/// <param name="list">
/// A list of
/// <see cref="Edu.Stanford.Nlp.Util.ICoreMap"/>
/// s representing a single document.
/// Note: We assume the NERs has been labelled and the labels
/// will be updated in place.
/// </param>
/// <param name="document"/>
/// <param name="sentence"/>
/// <?/>
public static void AddNormalizedQuantitiesToEntities <E>(IList <E> list, ICoreMap document, ICoreMap sentence)
where E : ICoreMap
{
// Fix the NER sequence if necessay
FixupNerBeforeNormalization(list);
// Now that NER tags has been fixed up, we do another pass to add the normalization
string prevNerTag = BackgroundSymbol;
int beforeIndex = -1;
List <E> collector = new List <E>();
for (int i = 0; i <= sz; i++)
{
// we should always keep list.size() unchanged inside the loop
E wi = null;
string currNerTag = null;
string nextWord = string.Empty;
if (i < sz)
{
wi = list[i];
if (i + 1 < sz)
{
nextWord = list[i + 1].Get(typeof(CoreAnnotations.TextAnnotation));
if (nextWord == null)
{
nextWord = string.Empty;
}
}
// We assume NERs have been set by previous NER taggers
currNerTag = wi.Get(typeof(CoreAnnotations.NamedEntityTagAnnotation));
}
// TODO: may need to detect TIME modifier here?
E wprev = (i > 0) ? list[i - 1] : null;
// if the current wi is a non-continuation and the last one was a
// quantity, we close and process the last segment.
// TODO: also need to check compatibility as the English normalizer does
if ((currNerTag == null || !currNerTag.Equals(prevNerTag)) && quantifiable.Contains(prevNerTag))
{
string modifier = null;
switch (prevNerTag)
{
case TimeTag:
{
// Need different handling for different tags
// TODO: add TIME
break;
}
case DateTag:
{
ProcessEntity(collector, prevNerTag, modifier, nextWord, document);
break;
}
default:
{
if (prevNerTag.Equals(NumberTag) || prevNerTag.Equals(PercentTag) || prevNerTag.Equals(MoneyTag))
{
// we are doing for prev tag so afterIndex should really be i
modifier = DetectQuantityModifier(list, beforeIndex, i);
}
ProcessEntity(collector, prevNerTag, modifier, nextWord);
break;
}
}
collector = new List <E>();
}
// If currNerTag is quantifiable, we add it into collector
if (quantifiable.Contains(currNerTag))
{
if (collector.IsEmpty())
{
beforeIndex = i - 1;
}
collector.Add(wi);
}
// move on and update prev pointer
prevNerTag = currNerTag;
}
}
public virtual ICounter <string> GetTopSpeakers(IList <Sieve.MentionData> closestMentions, IList <Sieve.MentionData> closestMentionsBackward, Person.Gender gender, ICoreMap quote, bool overrideGender)
{
ICounter <string> topSpeakerInRange = new ClassicCounter <string>();
ICounter <string> topSpeakerInRangeIgnoreGender = new ClassicCounter <string>();
ICollection <Sieve.MentionData> backwardsMentions = new HashSet <Sieve.MentionData>(closestMentionsBackward);
foreach (Sieve.MentionData mention in closestMentions)
{
double weight = backwardsMentions.Contains(mention) ? BackwardWeight : ForwardWeight;
if (mention.type.Equals(Name))
{
if (!characterMap.Keys.Contains(mention.text))
{
continue;
}
Person p = characterMap[mention.text][0];
if ((gender == Person.Gender.Male && p.gender == Person.Gender.Male) || (gender == Person.Gender.Female && p.gender == Person.Gender.Female) || (gender == Person.Gender.Unk))
{
topSpeakerInRange.IncrementCount(p.name, weight);
}
topSpeakerInRangeIgnoreGender.IncrementCount(p.name, weight);
if (closestMentions.Count == 128 && closestMentionsBackward.Count == 94)
{
System.Console.Out.WriteLine(p.name + " " + weight + " name");
}
}
else
{
if (mention.type.Equals(Pronoun))
{
int charBeginKey = doc.Get(typeof(CoreAnnotations.TokensAnnotation))[mention.begin].BeginPosition();
Person p = DoCoreference(charBeginKey, quote);
if (p != null)
{
if ((gender == Person.Gender.Male && p.gender == Person.Gender.Male) || (gender == Person.Gender.Female && p.gender == Person.Gender.Female) || (gender == Person.Gender.Unk))
{
topSpeakerInRange.IncrementCount(p.name, weight);
}
topSpeakerInRangeIgnoreGender.IncrementCount(p.name, weight);
if (closestMentions.Count == 128 && closestMentionsBackward.Count == 94)
{
System.Console.Out.WriteLine(p.name + " " + weight + " pronoun");
}
}
}
}
}
if (topSpeakerInRange.Size() > 0)
{
return(topSpeakerInRange);
}
else
{
if (gender != Person.Gender.Unk && !overrideGender)
{
return(topSpeakerInRange);
}
}
return(topSpeakerInRangeIgnoreGender);
}
