Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction

Research article (Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022) · cited 76× · AI/ML
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Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction

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Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction. Retrieved May 24, 2026, from https://4ort.xyz/entity/revisiting-docred-addressing-the-false-negative-problem-in-relation-extraction
MLA “Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/revisiting-docred-addressing-the-false-negative-problem-in-relation-extraction.
BibTeX @misc{4ortxyz_revisiting-docred-addressing-the-false-negative-problem-in-relation-extraction_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction}}, year = {2026}, url = {https://4ort.xyz/entity/revisiting-docred-addressing-the-false-negative-problem-in-relation-extraction}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction — https://4ort.xyz/entity/revisiting-docred-addressing-the-false-negative-problem-in-relation-extraction (retrieved 2026-05-24)

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