Earticle

초록

영어

Typical Text-to-SQL research copes with the problem of parsing natural language questions into executable SQL queries. While new datasets emerge progressively, most are committed to exploring the robustness and generalizability of models, leaving the research of model's capability in solving geography-specific questions blank. To this end, in this work, we approach this problem by proposing an improved abstract syntax tree to represent spatial SQL queries. Following this proposition, we build SpatialSpider, a new Text-to-SQL dataset in the geography domain. Our dataset introduces the following challenges: 1) Understanding of geographical semantics. 2) Prediction of spatial functions. In summary, we propose an improved abstract syntax tree and a dataset to tackle the spatial Text-to-SQL problem and obtain promising experimental results.

목차

Abstract
I. INTRODUCTION
II. PROPOSED METHOD
III. DATASET CONSTRUCTION
A. Spatial Functions
B. Question/SQL Creation
IV. EXPERIMENT
V. CONCLUSION
REFERENCES

키워드

저자

• Feiyang Xiao [ Department of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing, China ] Corresponding author
• Jin Li [ Department of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004