Knowledge-enriched, type-constrained and grammar-guided question generation over knowledge bases

Sheng Bi, Xiya Chen, Yuan-Fang Li, Yongzhen Wang, Guilin Qi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Question generation over knowledge bases (KBQG) aims at generating natural-language ques- tions about a subgraph, i.e. a set of triples. Two main challenges still face the current crop of encoder-decoder-based methods, especially on small subgraphs: (1) low diversity and poor flu- ency due to the limited information contained in the subgraphs, and (2) semantic drift due to the decoder’s oblivion of the semantics of the answer entity. We propose an innovative knowledge- enriched, type-constrained and grammar-guided KBQG model, named KTG, to addresses the above challenges. In our model, the encoder is equipped with auxiliary information from the KB, and the decoder is constrained with word types during QG. Specifically, entity domain and description, as well as relation hierarchy information are considered to construct question contexts, while a conditional copy mechanism is incorporated to modulate question semantics according to current word types. Besides, a novel reward function featuring grammatical similar- ity is designed to improve both generative richness and syntactic correctness via reinforcement learning. Extensive experiments show that our proposed model outperforms existing methods by a significant margin on two widely-used benchmark datasets SimpleQuestion and PathQuestion.
Original languageEnglish
Title of host publicationCOLING 2020
Subtitle of host publicationThe 28th International Conference on Computational Linguistics, Proceedings of the Conference
EditorsNuria Bel, Chengqing Zong
Place of PublicationStroudsburg PA USA
PublisherAssociation for Computational Linguistics (ACL)
Pages2776-2786
Number of pages11
ISBN (Electronic)9781952148279
DOIs
Publication statusPublished - 2020
EventInternational Conference on Computational Linguistics 2020 - Virtual, Barcelona, Spain
Duration: 8 Dec 202013 Dec 2020
Conference number: 28th
https://coling2020.org (Website)
https://www.aclweb.org/anthology/volumes/2020.coling-main/ (Proceedings)

Conference

ConferenceInternational Conference on Computational Linguistics 2020
Abbreviated titleCOLING 2020
Country/TerritorySpain
CityBarcelona
Period8/12/2013/12/20
Internet address

Cite this