Papers › Nested Named Entity Recognition via Explicitly Excluding the Influence of the Best Path
Nested Named Entity Recognition via Explicitly Excluding the Influence of the Best Path
Yiran Wang, Hiroyuki Shindo, Yuji Matsumoto, Taro Watanabe
This paper presents a novel method for nested named entity recognition. As a layered method, our method extends the prior second-best path recognition method by explicitly excluding the influence of the best path. Our method maintains a set of hidden states at each time step and selectively leverages them to build a different potential function for recognition at each level. In addition, we demonstrate that recognizing innermost entities first results in better performance than the conventional outermost entities first scheme. We provide extensive experimental results on ACE2004, ACE2005, and GENIA datasets to show the effectiveness and efficiency of our proposed method.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Nested Named Entity Recognition | ACE 2004 | LogSumExpDecoder | F1 | 86.42 | #16 of 24 | Archive leaderboard | report |
| Nested Named Entity Recognition | ACE 2005 | LogSumExpDecoder | F1 | 84.93 | #13 of 25 | Archive leaderboard | report |
| Nested Named Entity Recognition | GENIA | LogSumExpDecoder | F1 | 78.93 | #13 of 26 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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