CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues

Deepanway Ghosal, Siqi Shen, Navonil Majumder, Rada Mihalcea, Soujanya Poria


Abstract
This paper addresses the problem of dialogue reasoning with contextualized commonsense inference. We curate CICERO, a dataset of dyadic conversations with five types of utterance-level reasoning-based inferences: cause, subsequent event, prerequisite, motivation, and emotional reaction. The dataset contains 53,105 of such inferences from 5,672 dialogues. We use this dataset to solve relevant generative and discriminative tasks: generation of cause and subsequent event; generation of prerequisite, motivation, and listener’s emotional reaction; and selection of plausible alternatives. Our results ascertain the value of such dialogue-centric commonsense knowledge datasets. It is our hope that CICERO will open new research avenues into commonsense-based dialogue reasoning.
Anthology ID:
2022.acl-long.344
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Smaranda Muresan, Preslav Nakov, Aline Villavicencio
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5010–5028
Language:
URL:
https://aclanthology.org/2022.acl-long.344
DOI:
10.18653/v1/2022.acl-long.344
Bibkey:
Cite (ACL):
Deepanway Ghosal, Siqi Shen, Navonil Majumder, Rada Mihalcea, and Soujanya Poria. 2022. CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5010–5028, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues (Ghosal et al., ACL 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/improve-issue-templates/2022.acl-long.344.pdf
Video:
 https://preview.aclanthology.org/improve-issue-templates/2022.acl-long.344.mp4
Code
 declare-lab/CICERO
Data
CICERODREAMDailyDialogMuTual