IRAC: A Domain-Specific Annotated Corpus of Implicit Reasoning in Arguments
Keshav Singh, Naoya Inoue, Farjana Sultana Mim, Shoichi Naito, Kentaro Inui
Abstract
The task of implicit reasoning generation aims to help machines understand arguments by inferring plausible reasonings (usually implicit) between argumentative texts. While this task is easy for humans, machines still struggle to make such inferences and deduce the underlying reasoning. To solve this problem, we hypothesize that as human reasoning is guided by innate collection of domain-specific knowledge, it might be beneficial to create such a domain-specific corpus for machines. As a starting point, we create the first domain-specific resource of implicit reasonings annotated for a wide range of arguments, which can be leveraged to empower machines with better implicit reasoning generation ability. We carefully design an annotation framework to collect them on a large scale through crowdsourcing and show the feasibility of creating a such a corpus at a reasonable cost and high-quality. Our experiments indicate that models trained with domain-specific implicit reasonings significantly outperform domain-general models in both automatic and human evaluations. To facilitate further research towards implicit reasoning generation in arguments, we present an in-depth analysis of our corpus and crowdsourcing methodology, and release our materials (i.e., crowdsourcing guidelines and domain-specific resource of implicit reasonings).- Anthology ID:
- 2022.lrec-1.499
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 4674–4683
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.499
- DOI:
- Cite (ACL):
- Keshav Singh, Naoya Inoue, Farjana Sultana Mim, Shoichi Naito, and Kentaro Inui. 2022. IRAC: A Domain-Specific Annotated Corpus of Implicit Reasoning in Arguments. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 4674–4683, Marseille, France. European Language Resources Association.
- Cite (Informal):
- IRAC: A Domain-Specific Annotated Corpus of Implicit Reasoning in Arguments (Singh et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.lrec-1.499.pdf
- Code
- cl-tohoku/irac_2022