摘要
为解决计算机理解和表达汉语句义的问题,以现代汉语语义学理论为基础,探索和创建了一种计算机可计算、可扩展的汉语句义结构模型,该模型从句义层次上描述构成句子的词、子句、分句在句义中承担的句义任务,句子描述对象的时空特征、谓词的时态以及不同句义成分之间的组合关系等,形成了一种抽象句义的结构化表达形式;同时,提出了一种基于反向提问的句义结构模型验证方法,用疑问词替换语义格迭代构成问句,再对问句进行评价.实验结果表明,对简单句义、复杂句义和多重句义的反向提问正确率达到92.07%,充分说明句义结构模型的合理性.
The requirement of deep language understanding is more and more important in the fields of information auto-processing and information security. To solve the difficulty of computer understanding Chinese sentential semantics, this paper proposes a computable and extensible Chinese sentential semantic mode （BFS-CSM）, which is based on the theory of modern Chinese semantics. In addition, a reversed question based sentential semantic structure method is put forward to verify the correctness of proposed BFS-CSM. Experimental results show that the precision of the verification method is 92.07% and the rationality of proposed mode is confirmed. This research provides a new way of thinking for Chinese natural language processing and has important applied value.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2013年第2期166-171,共6页
Transactions of Beijing Institute of Technology
基金
国家242项目(2005C48)
北京理工大学科技创新计划重大项目培育专项计划(2011CX01015)
北京理工大学研究生创新项目(GC200802)
关键词
句义结构模型
反向提问
汉语语义学
语义分析
自然语言处理
sentential semantic mode
reverse questions
Chinese semantics
sentential semantic analysis
natural language processing
