CRFs-Based Named Entity Recognition Incorporated with Heuristic Entity List Searching
نویسندگان
چکیده
Chinese Named entity recognition is one of the most important tasks in NLP. Two kinds of Challenges we confront are how to improve the performance in one corpus and keep its performance in another different corpus. We use a combination of statistical models, i.e. a language model to recognize person names and two CRFs models to recognize Location names and Organization names respectively. We also incorporate an efficient heuristic named entity list searching process into the framework of statistical model in order to improve both the performance and the adaptability of the statistical NER system. We participate in the NER tests on open tracks of MSRA. The testing results show that our system can performs well.
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