Nested Named Entity Recognition via Explicitly Excluding the Influence of the Best Path
Yiran Wang, Hiroyuki Shindo, Yuji Matsumoto, Taro Watanabe
摘要
This paper presents a novel method for nested named entity recognition.
As a layered method, our method extends the prior secondbest 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.
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