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Domain-Specific NER via Retrieving Correlated Samples. (arXiv:2208.12995v3 [cs.CL] UPDATED)
Sept. 29, 2022, 1:15 a.m. | Xin Zhang, Yong Jiang, Xiaobin Wang, Xuming Hu, Yueheng Sun, Pengjun Xie, Meishan Zhang
cs.CL updates on arXiv.org arxiv.org
Successful Machine Learning based Named Entity Recognition models could fail
on texts from some special domains, for instance, Chinese addresses and
e-commerce titles, where requires adequate background knowledge. Such texts are
also difficult for human annotators. In fact, we can obtain some potentially
helpful information from correlated texts, which have some common entities, to
help the text understanding. Then, one can easily reason out the correct answer
by referencing correlated samples. In this paper, we suggest enhancing NER
models with …
More from arxiv.org / cs.CL updates on arXiv.org
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