Few-NERD

홈페이지 · 논문 77편

Few-NERD is a large-scale, fine-grained manually annotated named entity recognition dataset, which contains 8 coarse-grained types, 66 fine-grained types, 188,200 sentences, 491,711 entities, and 4,601,223 tokens. Three benchmark tasks are built, one is supervised (Few-NERD (SUP)) and the other two are few-shot (Few-NERD (INTRA) and Few-NERD (INTER)).

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벤치마크

Few-shot NER on Few-NERD (INTER) 결과 13개

Few-shot NER on Few-NERD (INTRA) 결과 13개

Named Entity Recognition (NER) on Few-NERD (SUP) 결과 6개