Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension

Jialin Chen, Zhuosheng Zhang, Hai Zhao


Abstract
Machine reading comprehension (MRC) poses new challenges to logical reasoning, which aims to understand the implicit logical relations entailed in the given contexts and perform inference over them. Due to the complexity of logic, logical connections exist at different granularity levels. However, most existing methods of logical reasoning individually focus on either entity-aware or discourse-based information but ignore the hierarchical relations that may even have mutual effects. This paper proposes a holistic graph network (HGN) that deals with context at both discourse-level and word-level as the basis for logical reasoning to provide a more fine-grained relation extraction. Specifically, node-level and type-level relations, which can be interpreted as bridges in the reasoning process, are modeled by a hierarchical interaction mechanism to improve the interpretation of MRC systems. Experimental results on logical reasoning QA datasets (ReClor and LogiQA) and natural language inference datasets (SNLI and ANLI) show the effectiveness and generalization of our method, and in-depth analysis verifies its capability to understand complex logical relations.
Anthology ID:
2022.coling-1.126
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
1467–1479
Language:
URL:
https://aclanthology.org/2022.coling-1.126
DOI:
Bibkey:
Cite (ACL):
Jialin Chen, Zhuosheng Zhang, and Hai Zhao. 2022. Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension. In Proceedings of the 29th International Conference on Computational Linguistics, pages 1467–1479, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension (Chen et al., COLING 2022)
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PDF:
https://aclanthology.org/2022.coling-1.126.pdf
Data
ANLILogiQAMuTualReClorSNLI