Question decomposition type semantic parsing method fusing fact text

Abstract

The invention relates to a question decomposition type semantic analysis method fusing a fact text, and belongs to the technical field of natural language processing. The method comprises the following steps of: dividing into three stages of decomposition, extraction and analysis, firstly decomposing a complex problem into a simple sub-problem sequence, then extracting key information in an original problem and the sub-problems, and finally generating a structured query statement by integrating the information. Meanwhile, in order to avoid the situation of entity judgment errors or subject entity missing in the decomposition process, triples in the knowledge base are converted into fact text information described by a natural language, a fact text base is constructed, an attention mechanism is adopted to obtain richer knowledge, and the purposes of enhancing entity representation information and reducing error propagation are achieved. According to the method, the fact text information is fused, semantic analysis is carried out on the complex problem by adopting a question decomposition mode, the understanding ability of the question and answer model on the complex problem is improved, and therefore the problem that the processing effect of a knowledge base question and answer technology on the complex problem is poor is solved.

Description

technical field [0001] The invention relates to a decomposing semantic parsing method for question sentences fused with factual texts, and belongs to the technical field of natural language processing. Background technique [0002] Knowledge base question answering technology aims to find answers to questions from pre-established structured knowledge bases, and has become one of the research hotspots in academia and industry due to its wide range of application scenarios and huge application value. With the continuous development of knowledge base construction technology, the scale of knowledge base is getting larger and larger, such as Freebase, DBpedia, Wikidata and other large knowledge bases store a wealth of related knowledge, which provides a data foundation for knowledge base question and answer. [0003] However, most of the current question answering systems can only answer factual questions, cannot handle complex questions well, and are difficult to understand the ...

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Problems solved by technology

[0007] The technical problem to be solved by the present invention is: the present invention provides a question-sentence-decomposed semantic analysis method that integrates factual texts, so as to solve the problem that the model wrongly judges or loses the question sentences in the process of decomposing complex questions into simple question sequences. The problem of subject entities; solves the problem that when the knowledge base question answering technology faces complex questions, the model cannot accurately parse the complex semantics in the question sentences, resulting in poor performance of the question answering system

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