Cloze Evaluation for Deeper Understanding of Commonsense Stories in Indonesian
Document Type
Conference Proceeding
Publication Title
CSRR 2022 - 1st Workshop on Commonsense Representation and Reasoning
Abstract
Story comprehension that involves complex causal and temporal relations is a critical task in NLP, but previous studies have focused predominantly on English, leaving open the question of how the findings generalize to other languages, such as Indonesian. In this paper, we follow the Story Cloze Test framework of Mostafazadeh et al. (2016) in evaluating story understanding in Indonesian, by constructing a four-sentence story with one correct ending and one incorrect ending. To investigate commonsense knowledge acquisition in language models, we experimented with: (1) a classification task to predict the correct ending; and (2) a generation task to complete the story with a single sentence. We investigate these tasks in two settings: (i) monolingual training and (ii) zero-shot cross-lingual transfer between Indonesian and English. © 2022 Association for Computational Linguistics.
First Page
8
Last Page
16
DOI
10.18653/v1/2022.csrr-1.2
Publication Date
5-2022
Keywords
Classification (of information), Computational linguistics, Natural language processing systems
Recommended Citation
F. Koto, T. Baldwin, and J.H. Lau, "Cloze Evaluation for Deeper Understanding of Commonsense Stories in Indonesian", in Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022), May 2022, pp. 8–16, doi:10.18653/v1/2022.csrr-1.2
Comments
IR Deposit conditions: non-described