a7949425b0ff59786c9baf976e112ac2e07f3f77,nalaf/learning/taggers.py,StubSameSentenceRelationExtractor,annotate,#StubSameSentenceRelationExtractor#Any#,131

Before Change

    def annotate(self, dataset):
            from itertools import product
            for part in dataset.parts():
                for ann_1, ann_2 in product(
                        (ann for ann in part.annotations if ann.class_id == self.entity1_class),
                        (ann for ann in part.annotations if ann.class_id == self.entity2_class)):
                    if part.get_sentence_index_for_annotation(ann_1) == part.get_sentence_index_for_annotation(ann_2):
                        part.predicted_relations.append(
                            Relation(ann_1.offset, ann_2.offset, ann_1.text, ann_2.text, self.relation_type))

After Change

        self.sentence_splitter.split(dataset)
        self.tokenizer.tokenize(dataset)

        for document in dataset:
            for part in document:
                for ann_1, ann_2 in product(
                    (a for a in part.annotations if a.class_id == self.entity1_class),
                    (a for a in part.annotations if a.class_id == self.entity2_class)):

                    if part.get_sentence_index_for_annotation(ann_1) == part.get_sentence_index_for_annotation(ann_2):
                        rel = Relation(ann_1.offset, ann_2.offset, ann_1.text, ann_2.text, self.relation_type)
                        part.predicted_relations.append(rel)


class StubSameDocumentPartRelationExtractor(RelationExtractor):

    def __init__(self, entity1_class, entity2_class, relation_type):
        super().__init__(entity1_class, entity2_class, relation_type)

Instances