MuG-QA: Multilingual Grammatical Question Answering for RDF Data

E. Zimina, J. Nummenmaa, K. Jarvelin, J. Peltonen, K. Stefanidis
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引用次数: 3

Abstract

We introduce Multilingual Grammatical Question Answering (MuG-QA), a system for answering questions in the English, German, Italian and French languages over DBpedia. The natural language modelling and parsing is implemented using Grammatical Framework (GF), a grammar formalism having natural support for multilinguality. The question analysis is based on forming an abstract conceptual grammar from the questions, and then using linearisation of the abstract grammar into different languages to parse the questions. Once a natural language question is parsed, the resulting abstract grammar tree is matched with the knowledge base schema and contents to formulate a SPARQL query. A particular strength of our approach is that once the abstract grammar has been designed, implementation for a new concrete language is relatively quick, supposing that the language has basic support in the GF Resource Grammar Library. MuG-QA has been tested with data from the QALD-7 benchmark and showed competitive results.
RDF数据的多语言语法问答
我们介绍了多语言语法问答(MuG-QA),这是一个在DBpedia上回答英语、德语、意大利语和法语问题的系统。自然语言建模和解析使用语法框架(GF)实现,GF是一种自然支持多语言的语法形式。问题分析是基于从问题中形成一个抽象的概念语法,然后使用抽象语法线性化成不同的语言来解析问题。一旦解析了自然语言问题,生成的抽象语法树就会与知识库模式和内容相匹配,从而形成SPARQL查询。我们的方法的一个特别的优点是,一旦抽象语法被设计出来,假设语言在GF资源语法库中有基本的支持,新的具体语言的实现就会相对较快。MuG-QA已经使用QALD-7基准测试的数据进行了测试,并显示出具有竞争力的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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