Abstract
Idiomatic expressions (IE) play an important role in natural language, and have long been a “pain in the neck” for NLP systems. Despite this, text generation tasks related to IEs remain largely under-explored. In this paper, we propose two new tasks of idiomatic sentence generation and paraphrasing to fill this research gap. We introduce a curated dataset of 823 IEs, and a parallel corpus with sentences containing them and the same sentences where the IEs were replaced by their literal paraphrases as the primary resource for our tasks. We benchmark existing deep learning models, which have state-of-the-art performance on related tasks using automated and manual evaluation with our dataset to inspire further research on our proposed tasks. By establishing baseline models, we pave the way for more comprehensive and accurate modeling of IEs, both for generation and paraphrasing.- Anthology ID:
- 2021.mwe-1.5
- Volume:
- Proceedings of the 17th Workshop on Multiword Expressions (MWE 2021)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Paul Cook, Jelena Mitrović, Carla Parra Escartín, Ashwini Vaidya, Petya Osenova, Shiva Taslimipoor, Carlos Ramisch
- Venue:
- MWE
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 33–48
- Language:
- URL:
- https://aclanthology.org/2021.mwe-1.5
- DOI:
- 10.18653/v1/2021.mwe-1.5
- Cite (ACL):
- Jianing Zhou, Hongyu Gong, and Suma Bhat. 2021. PIE: A Parallel Idiomatic Expression Corpus for Idiomatic Sentence Generation and Paraphrasing. In Proceedings of the 17th Workshop on Multiword Expressions (MWE 2021), pages 33–48, Online. Association for Computational Linguistics.
- Cite (Informal):
- PIE: A Parallel Idiomatic Expression Corpus for Idiomatic Sentence Generation and Paraphrasing (Zhou et al., MWE 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2021.mwe-1.5.pdf
- Data
- WikiLarge