A Little Pretraining Goes a Long Way: A Case Study on Dependency Parsing Task for Low-resource Morphologically Rich Languages
Jivnesh Sandhan, Amrith Krishna, Ashim Gupta, Laxmidhar Behera, Pawan Goyal
Abstract
Neural dependency parsing has achieved remarkable performance for many domains and languages. The bottleneck of massive labelled data limits the effectiveness of these approaches for low resource languages. In this work, we focus on dependency parsing for morphological rich languages (MRLs) in a low-resource setting. Although morphological information is essential for the dependency parsing task, the morphological disambiguation and lack of powerful analyzers pose challenges to get this information for MRLs. To address these challenges, we propose simple auxiliary tasks for pretraining. We perform experiments on 10 MRLs in low-resource settings to measure the efficacy of our proposed pretraining method and observe an average absolute gain of 2 points (UAS) and 3.6 points (LAS).- Anthology ID:
- 2021.eacl-srw.16
- Volume:
- Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Editors:
- Ionut-Teodor Sorodoc, Madhumita Sushil, Ece Takmaz, Eneko Agirre
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 111–120
- Language:
- URL:
- https://aclanthology.org/2021.eacl-srw.16
- DOI:
- 10.18653/v1/2021.eacl-srw.16
- Cite (ACL):
- Jivnesh Sandhan, Amrith Krishna, Ashim Gupta, Laxmidhar Behera, and Pawan Goyal. 2021. A Little Pretraining Goes a Long Way: A Case Study on Dependency Parsing Task for Low-resource Morphologically Rich Languages. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 111–120, Online. Association for Computational Linguistics.
- Cite (Informal):
- A Little Pretraining Goes a Long Way: A Case Study on Dependency Parsing Task for Low-resource Morphologically Rich Languages (Sandhan et al., EACL 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2021.eacl-srw.16.pdf
- Code
- Jivnesh/LCM
- Data
- Universal Dependencies