Fantastic Expressions and Where to Find Them: Chinese Simile Generation with Multiple Constraints

Kexin Yang, Dayiheng Liu, Wenqiang Lei, Baosong Yang, Xiangpeng Wei, Zhengyuan Liu, Jun Xie


Abstract
Similes occur in the creative context of describing a concept (i.e., tenor) by making a literally false yet figuratively meaningful comparison to another (i.e., vehicle). Previous efforts form simile generation as a context-free generation task, focusing on simile-style transfer or writing a simile from a given prefix. However, generated texts under such settings might be undesirable, such as hardly meeting the simile definition (e.g., missing vehicle) or difficult to address certain preferences of content as humans wish (e.g., describe the color of apples through the simile). We believe that a simile could be more qualified and user-oriented if incorporated with pre-specified constraints. To this end, we introduce controllable simile generation (CSG), a new task that requires the model to generate a simile with multiple simile elements, e.g., context and vehicle. To facilitate this task, we present GraCe, including 61.3k simile-element annotated Chinese similes. Based on it, we propose a CSG model Similor to benchmark this task, including a vehicle retrieval module Scorer to obtain the explicable comparison for a given tenor in the vehicle-unknown situation. Both statistical and experimental analyses show that GraCe is of high quality beyond all other Chinese simile datasets, in terms of the number (8 vs. 3) of annotation elements, Is-Simile accuracy (98.9% vs. 78.7%), and increasing model-performance gains for both uncontrollable and controllable simile generation. Meanwhile, Similor can serve as a strong baseline for CSG, especially with Scorer, which beats model-based retrieval methods without any re-training.
Anthology ID:
2023.acl-long.28
Volume:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
468–486
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/2023.acl-long.28/
DOI:
10.18653/v1/2023.acl-long.28
Bibkey:
Cite (ACL):
Kexin Yang, Dayiheng Liu, Wenqiang Lei, Baosong Yang, Xiangpeng Wei, Zhengyuan Liu, and Jun Xie. 2023. Fantastic Expressions and Where to Find Them: Chinese Simile Generation with Multiple Constraints. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 468–486, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Fantastic Expressions and Where to Find Them: Chinese Simile Generation with Multiple Constraints (Yang et al., ACL 2023)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/2023.acl-long.28.pdf
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 https://preview.aclanthology.org/build-pipeline-with-new-library/2023.acl-long.28.mp4