Dianqing Liu1,2, Lanqiu Zhang1,2, Yanqiu Shao1,2,*, Junzhao Sun3
Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 447-458, 2021, DOI:10.32604/iasc.2021.016320
Abstract Chinese semantic dependency graph (CSDG) parsing aims to analyze the semantic relationship between words in a sentence. Since it is a deep semantic analysis task, the parser needs a lot of prior knowledge about the real world to distinguish different semantic roles and determine the range of the head nodes of each word. Existing CSDG parsers usually use part-of-speech (POS) and lexical features, which can only provide linguistic knowledge, but not semantic knowledge about the word. To solve this problem, we propose an entity recognition method based on distant supervision and entity classification to recognize entities in sentences, and then… More >
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