@inproceedings{jiatong-kui-2024-mfe,
    title = "{MFE}-{NER}: Multi-feature Fusion Embedding for {C}hinese Named Entity Recognition",
    author = "Jiatong, Li  and
      Kui, Meng",
    editor = "Sun, Maosong  and
      Liang, Jiye  and
      Han, Xianpei  and
      Liu, Zhiyuan  and
      He, Yulan",
    booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)",
    month = jul,
    year = "2024",
    address = "Taiyuan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.ccl-1.86/",
    pages = "1112--1122",
    language = "eng",
    abstract = "``In Chinese Named Entity Recognition, character substitution is a complicated linguistic phe-nomenon. Some Chinese characters are quite similar as they share the same components or havesimilar pronunciations. People replace characters in a named entity with similar characters togenerate a new collocation but refer to the same object. As a result, it always leads to unrecog-nizable or mislabeling errors in the NER task. In this paper, we propose a lightweight method,MFE-NER, which fuses glyph and phonetic features to help pre-trained language models handlethe character substitution problem in the NER task with limited extra cost. Basically, in the glyphdomain, we disassemble Chinese characters into Five-Stroke components to represent structurefeatures. In the phonetic domain, an improved phonetic system is proposed in our work, makingit reasonable to describe phonetic similarity among Chinese characters. Experiments demon-strate that our method performs especially well in detecting character substitutions while slightlyimproving the overall performance of Chinese NER.''"
}