计算机应用与软件2024，Vol.41Issue(7)：184-191,8.DOI:10.3969/j.issn.1000-386x.2024.07.028
融合字段类型与文本匹配的中文问句解析
CHINESE QUESTION PARSING BASED ON FIELD TYPES AND TEXT MATCHING
纪相存 1李大林 2彭晓东2
作者信息
- 1. 中国科学院国家空间科学中心 北京 101499||中国科学院大学 北京 100049
- 2. 中国科学院国家空间科学中心 北京 101499
- 折叠
摘要
Abstract
Translating natural language questions to SQL statements can help more users to obtain what they want from the database.The protection of table content by the English dataset WikiSQL limits the migration and use of the model to a certain extent.In order to solve this problem,this paper proposes a Chinese question parsing methods combining the field types with text matching.The task was decomposed based on the SQL structure.The table structure information was combined into the input of the Roberta encoder through the column separators related to the field types.The text matching method combining the edit distance and semantic dictionary was used to make the model more robust.This method was tested on the more difficult Chinese dataset TableQA.The accuracy rate was up to 93.44％and the result verified that the method was efficient.关键词
自然语言转SQL语句/表结构信息/SQL结构/文本匹配Key words
Natural language to SQL statements/Table structure/SQL structure/Text matching分类
信息技术与安全科学引用本文复制引用
纪相存,李大林,彭晓东..融合字段类型与文本匹配的中文问句解析[J].计算机应用与软件,2024,41(7):184-191,8.
