Uses of Class
de.julielab.jnet.tagger.Sentence

Packages that use Sentence

Package	Description
de.julielab.jcore.ae.jnet.uima
de.julielab.jnet.tagger

Uses of Sentence in de.julielab.jcore.ae.jnet.uima

Methods in de.julielab.jcore.ae.jnet.uima that return Sentence

Modifier and Type	Method and Description
protected Sentence	EntityAnnotator.createUnitSentence(List<Token> tokenList, org.apache.uima.jcas.JCas JCas, ArrayList<HashMap<String,String>> metaList, JCoReCoverIndex<Abbreviation> abbreviationIndex, JCoReCoverIndex<Token> tokenIndex) Takes all info about meta data and generates the corresponding unit sequence represented by a Sentence object.
protected Sentence	EntityAnnotator.removeDuplicatedTokens(Sentence unitSentence) removes duplicate tokens in a unit sentence (i.e., tokens having the same offset position).

Methods in de.julielab.jcore.ae.jnet.uima with parameters of type Sentence

Modifier and Type	Method and Description
protected Sentence	EntityAnnotator.removeDuplicatedTokens(Sentence unitSentence) removes duplicate tokens in a unit sentence (i.e., tokens having the same offset position).
void	EntityAnnotator.writeToCAS(Sentence unitSentence, org.apache.uima.jcas.JCas aJCas, JCoReCoverIndex<Abbreviation> abbreviationIndex) creates the respective uima annotations from JNET's predictions.

Uses of Sentence in de.julielab.jnet.tagger

Methods in de.julielab.jnet.tagger that return Sentence

Modifier and Type	Method and Description
Sentence	NETagger.PPDtoUnits(String sentence) takes a sentence in piped format and returns the corresponding unit sentence as a Sentence object

Methods in de.julielab.jnet.tagger with parameters of type Sentence

Modifier and Type	Method and Description
void	NETagger.predict(Sentence sentence, boolean showSegmentConfidence) predicts the entity labels by means of a model.

Method parameters in de.julielab.jnet.tagger with type arguments of type Sentence

Modifier and Type	Method and Description
ArrayList<String>	NETagger.predictIOB(ArrayList<Sentence> sentences, boolean showSegmentConfidence) predict the entity labels by means of a previously learned model.
void	NETagger.train(ArrayList<Sentence> sentences) this is to train a NE model (based on CRF); when trained, the model is stored internally.

Constructor parameters in de.julielab.jnet.tagger with type arguments of type Sentence

Constructor and Description
SentencePipeIterator(ArrayList<Sentence> sentences)