Java Code Examples for edu.stanford.nlp.ling.IndexedWord#setOriginalText()
The following examples show how to use
edu.stanford.nlp.ling.IndexedWord#setOriginalText() .
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Example 1
| Source File: ImplicitExtractions.java From minie with GNU General Public License v3.0 | 5 votes |
|
/** Set the the relation to a is-a relation **/
public void setIsARelation() {
this.rel = new AnnotatedPhrase();
IndexedWord beWord = new IndexedWord();
beWord.setWord("is");
beWord.setOriginalText("is");
beWord.setTag(POS_TAG.VBZ);
beWord.setNER(NE_TYPE.NO_NER);
beWord.setLemma("be");
beWord.setValue("is");
beWord.setIndex(-2);
this.rel.addWordToList(beWord);
this.rel.setRoot(beWord);
}
Example 2
| Source File: MinIE.java From minie with GNU General Public License v3.0 | 4 votes |
|
/**
* Process possessives in the object.
* If we have ("SUBJ", "REL", "NP_1 POS NP_2"), then: ("SUBJ", "REL + NP_1 + of", "NP_2")
* @param prop: proposition (list of annotated phrases)
*/
public void processPoss(ObjectArrayList<AnnotatedPhrase> prop){
// If there's no object (clause type SV), return
if (prop.size() < 3)
return;
AnnotatedPhrase object = prop.get(2);
AnnotatedPhrase rel = prop.get(1);
TokenSequencePattern tPattern = TokenSequencePattern.compile(REGEX.T_NP_POS_NP);
TokenSequenceMatcher tMatcher = tPattern.getMatcher(object.getWordCoreLabelList());
int posIndex = -1;
while (tMatcher.find()){
List<CoreMap> match = tMatcher.groupNodes();
// Check if the first/last word of the match is the first/last word of the object
CoreLabel firstWord = new CoreLabel(match.get(0));
CoreLabel lastWord = new CoreLabel(match.get(match.size() - 1));
boolean check = false;
if (firstWord.index() == object.getWordList().get(0).index()){
if (lastWord.index() == object.getWordList().get(object.getWordList().size() - 1).index()){
check = true;
}
}
if (!check) break;
for (CoreMap cm: match){
CoreLabel cl = new CoreLabel(cm);
if (cl.tag().equals(POS_TAG.POS) && (cl.ner().equals(NE_TYPE.NO_NER))){
posIndex = object.getWordCoreLabelList().indexOf(cl);
break;
}
}
}
if (posIndex > -1){
IndexedWord of = new IndexedWord();
of.setOriginalText("of");
of.setLemma("of");
of.setWord("of");
of.setTag("IN");
of.setNER("O");
of.setIndex(-1);
ObjectArrayList<IndexedWord> pushedWords = new ObjectArrayList<>();
object.removeWordFromList(posIndex);
for (int i = posIndex; i < object.getWordList().size(); i++){
pushedWords.add(object.getWordList().get(i));
}
rel.addWordsToList(pushedWords);
rel.addWordToList(of);
object.removeWordsFromList(pushedWords);
}
}
Example 3
| Source File: ImplicitExtractions.java From minie with GNU General Public License v3.0 | 4 votes |
|
/** If ORG+ POS? NP PERSON+ => "PERSON" "is NP of" "ORG" (if there are , and or -> make multiple extractions) **/
public void extractPersonIsNPOfOrg() {
// Reusable variables
ObjectArrayList<AnnotatedPhrase> tempProp = new ObjectArrayList<>();
ObjectArrayList<AnnotatedPhrase> subjects = new ObjectArrayList<>();
IndexedWord subjRoot;
IndexedWord objRoot;
this.tPattern = TokenSequencePattern.compile(REGEX.T_ORG_NP_PERSON);
this.tMatcher = this.tPattern.getMatcher(CoreNLPUtils.getCoreLabelListFromIndexedWordList(this.sentence));
while (this.tMatcher.find()){
// Set the relation to be "is-a" relation
this.setIsARelation();
for (IndexedWord w: CoreNLPUtils.listOfCoreMapWordsToIndexedWordList(this.tMatcher.groupNodes())) {
if (w.ner().equals(NE_TYPE.PERSON))
this.subj.addWordToList(w);
else if (w.ner().equals(NE_TYPE.ORGANIZATION))
this.obj.addWordToList(w);
else if (w.tag().equals(POS_TAG.POS))
continue;
else if (w.lemma().equals(CHARACTER.COMMA) || w.lemma().equals("and") || w.lemma().equals("or")) {
subjRoot = CoreNLPUtils.getRootFromWordList(this.sentenceSemGraph, this.subj.getWordList());
subjects.add(new AnnotatedPhrase(this.subj.getWordList().clone(), subjRoot));
this.subj.clear();
}
else this.rel.addWordToList(w);
}
subjRoot = CoreNLPUtils.getRootFromWordList(this.sentenceSemGraph, this.subj.getWordList());
subjects.add(new AnnotatedPhrase(this.subj.getWordList().clone(), subjRoot));
objRoot = CoreNLPUtils.getRootFromWordList(this.sentenceSemGraph, this.obj.getWordList());
IndexedWord ofWord = new IndexedWord();
ofWord.setWord("of");
ofWord.setOriginalText("of");
ofWord.setTag(POS_TAG.IN);
ofWord.setNER(NE_TYPE.NO_NER);
ofWord.setLemma("of");
ofWord.setValue("of");
ofWord.setIndex(-2);
this.rel.addWordToList(ofWord);
for (AnnotatedPhrase subject: subjects) {
// Add the subj/rel/obj to the temporary proposition and then to the real propositions
subjRoot = CoreNLPUtils.getRootFromWordList(this.sentenceSemGraph, subject.getWordList());
tempProp.add(new AnnotatedPhrase(subject.getWordList(), subjRoot));
tempProp.add(new AnnotatedPhrase(this.rel.getWordList().clone(), this.rel.getRoot()));
tempProp.add(new AnnotatedPhrase(this.obj.getWordList().clone(), objRoot));
this.propositions.add(new AnnotatedProposition(tempProp.clone(), new Attribution()));
tempProp.clear();
}
// Clean the variables
this.subj.clear();
this.obj.clear();
this.rel.clear();
}
}
Example 4
| Source File: ImplicitExtractions.java From minie with GNU General Public License v3.0 | 4 votes |
|
/** If (NP+ PERSON) => "PERSON" "is" "NP" **/
public void extractNounPerson() {
// Reusable variables
ObjectArrayList<AnnotatedPhrase> tempProp = new ObjectArrayList<>();
IndexedWord subjRoot;
IndexedWord objRoot;
// Set the relation to be "is-a" relation
this.setIsARelation();
this.tPattern = TokenSequencePattern.compile(REGEX.T_NP_PERSON);
this.tMatcher = this.tPattern.getMatcher(CoreNLPUtils.getCoreLabelListFromIndexedWordList(this.sentence));
while (this.tMatcher.find()){
for (IndexedWord w: CoreNLPUtils.listOfCoreMapWordsToIndexedWordList(this.tMatcher.groupNodes())) {
if (w.ner().equals(NE_TYPE.PERSON)) {
this.subj.addWordToList(w);
}
else {
if (w.lemma().toLowerCase().equals("mrs.") || w.lemma().toLowerCase().equals("ms.") ||
w.lemma().toLowerCase().equals("mrs") || w.lemma().toLowerCase().equals("ms")) {
IndexedWord female = new IndexedWord();
female.setWord("female");
female.setOriginalText("female");
female.setTag(POS_TAG.NN);
female.setNER(NE_TYPE.NO_NER);
female.setLemma("female");
female.setValue("female");
female.setIndex(-2);
this.obj.addWordToList(female);
}
else if (w.lemma().toLowerCase().equals("mr.") || w.lemma().toLowerCase().equals("mr")) {
IndexedWord male = new IndexedWord();
male.setWord("male");
male.setOriginalText("male");
male.setTag(POS_TAG.NN);
male.setNER(NE_TYPE.NO_NER);
male.setLemma("male");
male.setValue("male");
male.setIndex(-2);
this.obj.addWordToList(male);
}
else if (Polarity.NEG_WORDS.contains(w.lemma().toLowerCase())) {
continue;
}
else {
this.obj.addWordToList(w);
}
}
}
// Add the subj/rel/obj to the temporary proposition and then to the real propositions
subjRoot = CoreNLPUtils.getRootFromWordList(this.sentenceSemGraph, this.subj.getWordList());
objRoot = CoreNLPUtils.getRootFromWordList(this.sentenceSemGraph, this.obj.getWordList());
tempProp.add(new AnnotatedPhrase(this.subj.getWordList().clone(), subjRoot));
tempProp.add(new AnnotatedPhrase(this.rel.getWordList().clone(), this.rel.getRoot()));
tempProp.add(new AnnotatedPhrase(this.obj.getWordList().clone(), objRoot));
this.propositions.add(new AnnotatedProposition(tempProp.clone(), new Attribution()));
// Clean the variables
tempProp.clear();
this.subj.clear();
this.obj.clear();
}
// Clear the relation
this.rel.clear();
}
