Term and Condition Contract

Research on term and condition contracts focuses on automating the analysis of these complex legal documents to improve comprehension and identify potential ambiguities or inconsistencies. Current efforts leverage natural language processing (NLP) techniques, including large language models (LLMs) and various machine learning algorithms like SVMs and BERT-based models, to classify clause types, detect potentially unfair or void clauses, and generate clarification questions. This work aims to assist both legal professionals in efficiently reviewing contracts and non-legal stakeholders in understanding their obligations, ultimately improving contract clarity and reducing disputes.