IITK@LCP at SemEval-2021 Task 1: Classification for Lexical Complexity Regression Task
Neil Shirude, Sagnik Mukherjee, Tushar Shandhilya, Ananta Mukherjee, Ashutosh Modi
Abstract
This paper describes our contribution to SemEval 2021 Task 1 (Shardlow et al., 2021): Lexical Complexity Prediction. In our approach, we leverage the ELECTRA model and attempt to mirror the data annotation scheme. Although the task is a regression task, we show that we can treat it as an aggregation of several classification and regression models. This somewhat counter-intuitive approach achieved an MAE score of 0.0654 for Sub-Task 1 and MAE of 0.0811 on Sub-Task 2. Additionally, we used the concept of weak supervision signals from Gloss-BERT in our work, and it significantly improved the MAE score in Sub-Task 1.- Anthology ID:
- 2021.semeval-1.66
- Volume:
- Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 541–547
- Language:
- URL:
- https://aclanthology.org/2021.semeval-1.66
- DOI:
- 10.18653/v1/2021.semeval-1.66
- Cite (ACL):
- Neil Shirude, Sagnik Mukherjee, Tushar Shandhilya, Ananta Mukherjee, and Ashutosh Modi. 2021. IITK@LCP at SemEval-2021 Task 1: Classification for Lexical Complexity Regression Task. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 541–547, Online. Association for Computational Linguistics.
- Cite (Informal):
- IITK@LCP at SemEval-2021 Task 1: Classification for Lexical Complexity Regression Task (Shirude et al., SemEval 2021)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2021.semeval-1.66.pdf