论文标题
从句法结构到语义关系：使用语音信息的一部分从复发的神经网络中提取超nym
From syntactic structure to semantic relationship: hypernym extraction from definitions by recurrent neural networks using the part of speech information
论文作者
论文摘要
Hypernym关系是语义网络中的重要元素。从定义中识别高nym是自然语言处理和语义分析中的重要任务。尽管WordNet之类的公共字典用于通用单词，但其在特定于领域的方案中的应用是有限的。现有的高鼻萃取工具要么依赖于特定的语义模式，要么集中于单词表示，这都证明了某些局限性。
The hyponym-hypernym relation is an essential element in the semantic network. Identifying the hypernym from a definition is an important task in natural language processing and semantic analysis. While a public dictionary such as WordNet works for common words, its application in domain-specific scenarios is limited. Existing tools for hypernym extraction either rely on specific semantic patterns or focus on the word representation, which all demonstrate certain limitations.
