从自然语言问题生成SPARQL查询的评估。
Evaluation of SPARQL query generation from natural language questions.
作者信息
Cohen K Bretonnel, Kim Jin-Dong
机构信息
Computational Bioscience Program U. Colorado School of Medicine.
Database Center for Life Science.
出版信息
Proc Conf Assoc Comput Linguist Meet. 2013 Sep;2013:3-7.
SPARQL queries have become the standard for querying linked open data knowledge bases, but SPARQL query construction can be challenging and time-consuming even for experts. SPARQL query generation from natural language questions is an attractive modality for interfacing with LOD. However, how to evaluate SPARQL query generation from natural language questions is a mostly open research question. This paper presents some issues that arise in SPARQL query generation from natural language, a test suite for evaluating performance with respect to these issues, and a case study in evaluating a system for SPARQL query generation from natural language questions.
SPARQL查询已成为查询链接开放数据知识库的标准，但即使对于专家来说，SPARQL查询构建也可能具有挑战性且耗时。从自然语言问题生成SPARQL查询是与链接开放数据进行交互的一种有吸引力的方式。然而，如何评估从自然语言问题生成SPARQL查询在很大程度上仍是一个开放的研究问题。本文提出了从自然语言生成SPARQL查询时出现的一些问题、一个用于评估针对这些问题的性能的测试套件，以及一个评估从自然语言问题生成SPARQL查询系统的案例研究。
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