class LearningBasedInformationExtractor(TaggerI): def train(self, sentences, model_file='resources/extractor.model'): self.tagger = IOBTagger(patterns=[ '*', '*:tl1=%X[-1,1]', '*:t=%X[0,1]', '*:tr1=%X[1,1]', '*:cp=%m[0,2,"..$"]', '*:c=%X[0,2]', '*:c0l1=%X[-1,2]/%X[0,2]', '*:c0r1=%X[0,2]/%X[1,2]', '*:cl1=%X[-1,2]', '*:cl2=%X[-2,2]', '*:cr1=%X[1,2]', '*:cr2=%X[2,2]', ]) self.tagger.train(sentences) self.tagger.save_model(model_file) def tag(self, sent): return self.tagger.tag(sent)
