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Corpus-based Pattern Induction for a Knowledge-based Question Answering Approach

机译:基于语料库的模式归纳为基于知识的问答方法

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In this paper, we present an approach which, given a knowledge base and an appropriate text corpus, automatically induces patterns which can be used to query the knowledge base. We do not only consider simple questions but text problems consisting of several sentences. Answers to complex text problems are determined by an inference process which computes the answer on the basis of the background knowledge in the knowledge base (KB) as well as the textual description of the problem. The question formulated in natural language thus needs to be translated into appropriate KB structures and queries. Our approach to translating the natural language question uses an underlying corpus and the knowledge base to derive meaningful and relevant patterns which can then be used to process the questions and capture their meaning with respect to the underlying knowledge base. We apply our approach to Advanced Placement (AP) questions in three areas: physics, chemistry and biology. We report results of a first evaluation of the translation procedure for the three domains.
机译:在本文中,我们提出了一种方法,该方法在给定知识库和适当的文本语料库的情况下,自动生成可用于查询知识库的模式。我们不仅考虑简单的问题,还考虑由几个句子组成的文本问题。复杂文本问题的答案由推理过程确定,该推理过程根据知识库(KB)中的背景知识以及问题的文本描述来计算答案。因此,需要将以自然语言提出的问题翻译成适当的知识库结构和查询。我们翻译自然语言问题的方法是使用基础语料库和知识库来导出有意义和相关的模式,然后可以使用这些模式来处理问题并针对基础知识捕获其含义。我们将我们的方法应用于物理,化学和生物学三个领域的高级选修(AP)问题。我们报告了对这三个域的翻译程序的首次评估结果。

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