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A Unified Generative Framework for Various NER Subtasks

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NERBART_生成式的文章

A Unified Generative Framework for Various NER Subtasks ACL-ICJNLP2021 paper A Unified Generative Framework for Various NER Subtasks github:https://github.com/yhcc/BARTNER

三种ner的格式,该文章想统一一下解决,就想到了生成式。

模型的输入和输出格式
  • X = [x1, x2, ..., xn] 即一个普通的句子。

  • Y = [s11, e11, ..., s1j, e1j, t1, ..., si1, ei1, ..., sik, eik, ti],

    each entity is represented as [si1, ei1, ..., sij, eij, ti]

    也就是说ti i表示实体的个数,然后,它前面的s e 分别表示i这个实体的开始位置额结束位置,因为有实体是被其他词分开的,所以需要有多个。 (也就是期望模型输出的格式)

实现复杂的指针,修改decoder和encoder在这里:https://github.com/yhcc/BARTNER/blob/main/model/bart.py

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