Unseen Entity Handling in Complex Question Answering over Knowledge Base via Language Generation

Xin Huang, Jung-Jae Kim, Bowei Zou


Abstract
Complex question answering over knowledge base remains as a challenging task because it involves reasoning over multiple pieces of information, including intermediate entities/relations and other constraints. Previous methods simplify the SPARQL query of a question into such forms as a list or a graph, missing such constraints as “filter” and “order_by”, and present models specialized for generating those simplified forms from a given question. We instead introduce a novel approach that directly generates an executable SPARQL query without simplification, addressing the issue of generating unseen entities. We adapt large scale pre-trained encoder-decoder models and show that our method significantly outperforms the previous methods and also that our method has higher interpretability and computational efficiency than the previous methods.
Anthology ID:
2021.findings-emnlp.50
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2021
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
Findings
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
547–557
Language:
URL:
https://aclanthology.org/2021.findings-emnlp.50
DOI:
10.18653/v1/2021.findings-emnlp.50
Bibkey:
Cite (ACL):
Xin Huang, Jung-Jae Kim, and Bowei Zou. 2021. Unseen Entity Handling in Complex Question Answering over Knowledge Base via Language Generation. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 547–557, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Unseen Entity Handling in Complex Question Answering over Knowledge Base via Language Generation (Huang et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-emnlp.50.pdf
Video:
 https://aclanthology.org/2021.findings-emnlp.50.mp4
Data
ComplexWebQuestionsMetaQA