Abstract
Universal Semantic Tagging aims to provide lightweight unified analysis for all languages at the word level. Though the proposed annotation scheme is conceptually promising, the feasibility is only examined in four Indo–European languages. This paper is concerned with extending the annotation scheme to handle Mandarin Chinese and empirically study the plausibility of unifying meaning representations for multiple languages. We discuss a set of language-specific semantic phenomena, propose new annotation specifications and build a richly annotated corpus. The corpus consists of 1100 English–Chinese parallel sentences, where compositional semantic analysis is available for English, and another 1000 Chinese sentences which has enriched syntactic analysis. By means of the new annotations, we also evaluate a series of neural tagging models to gauge how successful semantic tagging can be: accuracies of 92.7% and 94.6% are obtained for Chinese and English respectively. The English tagging performance is remarkably better than the state-of-the-art by 7.7%.- Anthology ID:
- 2021.naacl-main.440
- Volume:
- Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tur, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, Yichao Zhou
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 5554–5566
- Language:
- URL:
- https://aclanthology.org/2021.naacl-main.440
- DOI:
- 10.18653/v1/2021.naacl-main.440
- Cite (ACL):
- Wenxi Li, Yiyang Hou, Yajie Ye, Li Liang, and Weiwei Sun. 2021. Universal Semantic Tagging for English and Mandarin Chinese. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5554–5566, Online. Association for Computational Linguistics.
- Cite (Informal):
- Universal Semantic Tagging for English and Mandarin Chinese (Li et al., NAACL 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2021.naacl-main.440.pdf
- Code
- pkucoli/ust