Revisiting Distant Supervision for Relation Extraction
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RelationRelation ExtractionSimilar Papers 제목 키워드 기반
Revisiting the Negative Data of Distantly Supervised Relation Extraction
Distantly supervision automatically generates plenty of training samples for relation extraction. However, it also incurs two major problems: noisy labels and imbalanced training data. Previous works focus more on reduci…
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Despite its popularity in sentence-level relation extraction, distantly supervised data is rarely utilized by existing work in document-level relation extraction due to its noisy nature and low information density. Among…
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Distant supervision for relation extraction heavily suffers from the wrong labeling problem. To alleviate this issue in news data with the timestamp, we take a new factor time into consideration and propose a novel time-…
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