Ceusters W, Spyns P, De Moor G
Language and Computing NV, Het Moorhof, Zonnegem, Belgium.
Int J Med Inform. 1998 Oct-Dec;52(1-3):149-57. doi: 10.1016/s1386-5056(98)00134-8.
In the GALEN project, the syntactic-semantic tagger MultiTALE is upgraded to extract knowledge from natural language surgical procedure expressions. In this paper, we describe the methodology applied and show that out of a randomly selected sample of such expressions coming from the procedure axis of Snomed International, 81% could be analysed correctly. The problems encountered fall in three different categories: unusual grammatical configurations within the Snomed terms, insufficient domain knowledge and different categorisation of concepts and semantic links in the domain and linguistic models used. It is concluded that the Multi-TALE system can be used to attach meaning to words that not have been encountered previously, but that an interface ontology mediating between domain models and linguistic models is needed to arrive at a higher level of independence from both particular languages and from particular domains.
在盖伦项目中，句法-语义标注器MultiTALE得到了升级，用于从自然语言手术过程表达中提取知识。在本文中，我们描述了所应用的方法，并表明从国际疾病分类法（SNOMED）的手术轴中随机抽取的此类表达样本中，81%能够被正确分析。遇到的问题分为三类：SNOMED术语中不寻常的语法结构、领域知识不足以及所使用的领域和语言模型中概念和语义链接的不同分类。得出的结论是，Multi-TALE系统可用于赋予以前未遇到的单词含义，但需要一个在领域模型和语言模型之间进行调解的接口本体，以实现更高程度地独立于特定语言和特定领域。
