A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering

Zhen Han, Yue Feng, Mingming Sun


Abstract
Recently, end-to-end trained models for multiple-choice commonsense question answering (QA) have delivered promising results. However, such question-answering systems cannot be directly applied in real-world scenarios where answer candidates are not provided. Hence, a new benchmark challenge set for open-ended commonsense reasoning (OpenCSR) has been recently released, which contains natural science questions without any predefined choices. On the OpenCSR challenge set, many questions require implicit multi-hop reasoning and have a large decision space, reflecting the difficult nature of this task. Existing work on OpenCSR sorely focuses on improving the retrieval process, which extracts relevant factual sentences from a textual knowledge base, leaving the important and non-trivial reasoning task outside the scope. In this work, we extend the scope to include a reasoner that constructs a question-dependent open knowledge graph based on retrieved supporting facts and employs a sequential subgraph reasoning process to predict the answer. The subgraph can be seen as a concise and compact graphical explanation of the prediction. Experiments on two OpenCSR datasets show that the proposed model achieves great performance on benchmark OpenCSR datasets.
Anthology ID:
2023.pandl-1.3
Volume:
Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning
Month:
December
Year:
2023
Address:
Singapore
Editors:
Mihai Surdeanu, Ellen Riloff, Laura Chiticariu, Dayne Frietag, Gus Hahn-Powell, Clayton T. Morrison, Enrique Noriega-Atala, Rebecca Sharp, Marco Valenzuela-Escarcega
Venues:
PANDL | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
20–24
Language:
URL:
https://aclanthology.org/2023.pandl-1.3
DOI:
10.18653/v1/2023.pandl-1.3
Bibkey:
Cite (ACL):
Zhen Han, Yue Feng, and Mingming Sun. 2023. A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering. In Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning, pages 20–24, Singapore. Association for Computational Linguistics.
Cite (Informal):
A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering (Han et al., PANDL-WS 2023)
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PDF:
https://aclanthology.org/2023.pandl-1.3.pdf
Video:
 https://aclanthology.org/2023.pandl-1.3.mp4