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Rewriting Natural Language Queries Using Patterns

机译：使用模式重写自然语言查询

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摘要

In this paper, a method based on pre-defined patterns, which rewrites natural language queries into a multi-layer, flexible, scalable and object-oriented query language, is presented. The method has been conceived to assist physicians in their search for clinical information in an Electronic Health Records system. Indeed, the query language of the system being difficult to handle for physicians, this method allows querying using natural language vs. using dedicated object-oriented query language. The information extraction method that has been developed can be seen as a named entity recognition system based on regular expressions that tags pieces of the query. The patterns are constructed recursively from the initial natural language query and from atomic patterns that correspond to the entities, the relationships and the constraints of the underlying model representing Electronic Health Records. Further evaluation is needed, but the preliminary results obtained by testing a set of natural language queries are very encouraging.
机译：本文提出了一种基于预定义模式的方法，该方法将自然语言查询重写为多层，灵活，可扩展且面向对象的查询语言。该方法被认为可以帮助医生在电子病历系统中搜索临床信息。实际上，该系统的查询语言对于医生而言难以处理，该方法允许使用自然语言进行查询，而不是使用专用的面向对象的查询语言进行查询。可以将已开发的信息提取方法看作是基于对查询片段进行标记的正则表达式的命名实体识别系统。这些模式是从初始自然语言查询以及与表示电子病历的基础模型的实体，关系和约束相对应的原子模式中递归构造的。需要进一步的评估，但是通过测试一组自然语言查询所获得的初步结果非常令人鼓舞。

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