Year: 2024
Type: conference-paper
Abstract: SCaLe-QA is a foundational system developed for Sri Lankan Legal Question Answering (LQA) by leveraging domain-specific embeddings derived from Supreme Court cases. The system is tailored to capture the unique linguistic and structural characteristics of Sri Lankan law through fine-tuned embeddings. While Case-Based Reasoning (CBR) will be integrated into the question-answering framework, it is primarily set for future development and evaluation. Currently, SCaLe-QA employs semantic chunking, tokenization, and BM25-based ranking to generate context-driven triplets from unlabeled corpora. In addition, an angle-optimised contrastive learning framework is applied to enhance retrieval accuracy. Preliminary results indicate promise, establishing SCaLe-QA as a significant step toward robust AI applications in the Sri Lankan legal domain.
Authors: Jayawardena, Lasal, Wiratunga, Nirmalie, Abeyratne, Ramitha, Martin, Kyle, Nkisi-Orji, Ikechukwu, Weerasinghe, Ruvan
Institutions: Robert Gordon University, Informatics Institute of Technology
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7033835846
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