中圖分類號(hào)：TP391 文獻(xiàn)標(biāo)志碼：A DOI: 10.16157/j.issn.0258-7998.233939 中文引用格式： 褚天舒，唐球,，梁軍學(xué),，等. 基于詞匯增強(qiáng)和表格填充的中文命名實(shí)體識(shí)別[J]. 電子技術(shù)應(yīng)用，2024,，50(2)：23-29. 英文引用格式： Chu Tianshu,，Tang Qiu，Liang Junxue,，et al. Chinese named entity recognition based on lexicon enhancement and table filling[J]. Application of Electronic Technique,，2024，50(2)：23-29.
Chinese named entity recognition based on lexicon enhancement and table filling
1.National Computer System Engineering Research Institute of China， Beijing 100083,， China,； 2.People′s Liberation Army 93216,， Beijing 100085， China
Abstract： Chinese named entity recognition has been involved with two tasks, including Chinese flat named entity recognition and Chinese nested named entity recognition. Chinese nested named entity recognition is more difficult. Therefore, this paper proposes a unified model, namely TLEXNER, based on lexicon enhancement and table filling, which can tackle the above two tasks concurrently. Aiming at the difficulty of Chinese word segmentation, the lexicon adapter is used to integrate the lexicon information into the BERT pre-training model,，and integrates the relative position information of characters and lexical groups into the BERT embedding layer. Then conditional layer normalization and biaffine model is used to build and predict the representation of the character-pair table, and the relationship between character pairs is modeled by table structure to obtain the unified representation of flat entities and nested entities.
Key words : lexicon enhancement,；Chinese named entity recognition；table filling
