As we may extract attitudes between objects that are mentioned anywhere in text, we still limited by a single sentence due to the related method API, which includes sentence_ind parameter.
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def _fill_row_core(self, row, linked_wrap, index_in_linked, etalon_label, |
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parsed_news, sentence_ind, s_ind, t_ind): |
And we rely on the source position of the (source,target) pair EntityEndType.Source:
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self._fill_row_core(row=row, |
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parsed_news=parsed_news, |
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sentence_ind=TextOpinionHelper.extract_entity_position( |
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parsed_news=parsed_news, |
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text_opinion=text_opinion, |
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end_type=EntityEndType.Source, |
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position_type=TermPositionTypes.SentenceIndex), |
As we may extract attitudes between objects that are mentioned anywhere in text, we still limited by a single sentence due to the related method API, which includes
sentence_indparameter.AREkit/arekit/common/experiment/input/formatters/sample.py
Lines 104 to 105 in 9b83f93
And we rely on the
sourceposition of the (source,target) pairEntityEndType.Source:AREkit/arekit/common/experiment/input/formatters/sample.py
Lines 158 to 164 in 9b83f93