LRG at SemEval-2021 Task 4: Improving Reading Comprehension with Abstract Words using Augmentation, Linguistic Features and Voting

Abheesht Sharma, Harshit Pandey, Gunjan Chhablani, Yash Bhartia, Tirtharaj Dash


Abstract
We present our approaches and methods for SemEval-2021 Task-4 Reading Comprehension of Abstract Meaning. Given a question with a fill-in-the-blank, and a corresponding context, the task is to predict the most suitable word from a list of 5 options. There are three subtasks: Imperceptibility, Non-Specificity and Intersection. We use encoders of transformers-based models pretrained on the MLM task to build our Fill-in-the-blank (FitB) models. Moreover, to model imperceptibility, we define certain linguistic features, and to model non-specificity, we leverage information from hypernyms and hyponyms provided by a lexical database. Specifically, for non-specificity, we try out augmentation techniques, and other statistical techniques. We also propose variants, namely Chunk Voting and Max Context, to take care of input length restrictions for BERT, etc. Additionally, we perform a thorough ablation study, and use Integrated Gradients to explain our predictions on a few samples. Our models achieve accuracies of 75.31% and 77.84%, on the test sets for subtask-I and subtask-II, respectively. For subtask-III, we achieve accuracies of 65.64% and 64.27%.
Anthology ID:
2021.semeval-1.21
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
189–198
Language:
URL:
https://aclanthology.org/2021.semeval-1.21
DOI:
10.18653/v1/2021.semeval-1.21
Bibkey:
Cite (ACL):
Abheesht Sharma, Harshit Pandey, Gunjan Chhablani, Yash Bhartia, and Tirtharaj Dash. 2021. LRG at SemEval-2021 Task 4: Improving Reading Comprehension with Abstract Words using Augmentation, Linguistic Features and Voting. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 189–198, Online. Association for Computational Linguistics.
Cite (Informal):
LRG at SemEval-2021 Task 4: Improving Reading Comprehension with Abstract Words using Augmentation, Linguistic Features and Voting (Sharma et al., SemEval 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.21.pdf
Code
 gchhablani/ReCAM