CSECU-DSG at SemEval-2023 Task 6: Segmenting Legal Documents into Rhetorical Roles via Fine-tuned Transformer Architecture
Abstract
Automated processing of legal documents is essential to manage the enormous volume of legal corpus and to make it easily accessible to a broad spectrum of people. But due to the amorphous and variable nature of legal documents, it is very challenging to directly proceed with complicated processes such as summarization, analysis, and query. Segmenting the documents as per the rhetorical roles can aid and accelerate such procedures. This paper describes our participation in SemEval-2023 task 6: Sub-task A: Rhetorical Roles Prediction. We utilize a finetuned Legal-BERT to address this task. We also conduct an error analysis to illustrate the shortcomings of our deployed approach.
Type
Publication
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Fareen Tasneem
Research Assistant (Full Time)
Tashin Hossain
Research Assistant (Full Time)
Jannatun Naim
Research Assistant (Full Time)
