ViNLI: A Vietnamese Corpus for Studies on Open-Domain Natural Language Inference

Tin Van Huynh, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen


Abstract
Over a decade, the research field of computational linguistics has witnessed the growth of corpora and models for natural language inference (NLI) for rich-resource languages such as English and Chinese. A large-scale and high-quality corpus is necessary for studies on NLI for Vietnamese, which can be considered a low-resource language. In this paper, we introduce ViNLI (Vietnamese Natural Language Inference), an open-domain and high-quality corpus for evaluating Vietnamese NLI models, which is created and evaluated with a strict process of quality control. ViNLI comprises over 30,000 human-annotated premise-hypothesis sentence pairs extracted from more than 800 online news articles on 13 distinct topics. In this paper, we introduce the guidelines for corpus creation which take the specific characteristics of the Vietnamese language in expressing entailment and contradiction into account. To evaluate the challenging level of our corpus, we conduct experiments with state-of-the-art deep neural networks and pre-trained models on our dataset. The best system performance is still far from human performance (a 14.20% gap in accuracy). The ViNLI corpus is a challenging corpus to accelerate progress in Vietnamese computational linguistics. Our corpus is available publicly for research purposes.
Anthology ID:
2022.coling-1.339
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:
3858–3872
Language:
URL:
https://aclanthology.org/2022.coling-1.339
DOI:
Bibkey:
Cite (ACL):
Tin Van Huynh, Kiet Van Nguyen, and Ngan Luu-Thuy Nguyen. 2022. ViNLI: A Vietnamese Corpus for Studies on Open-Domain Natural Language Inference. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3858–3872, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
ViNLI: A Vietnamese Corpus for Studies on Open-Domain Natural Language Inference (Huynh et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.339.pdf
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