[2603.01651] LexChronos: An Agentic Framework for Structured Event Timeline Extraction in Indian Jurisprudence

Computer Science > Computation and Language arXiv:2603.01651 (cs) [Submitted on 2 Mar 2026] Title:LexChronos: An Agentic Framework for Structured Event Timeline Extraction in Indian Jurisprudence Authors:Anka Chandrahas Tummepalli, Preethu Rose Anish View a PDF of the paper titled LexChronos: An Agentic Framework for Structured Event Timeline Extraction in Indian Jurisprudence, by Anka Chandrahas Tummepalli and 1 other authors View PDF HTML (experimental) Abstract:Understanding and predicting judicial outcomes demands nuanced analysis of legal documents. Traditional approaches treat judgments and proceedings as unstructured text, limiting the effectiveness of large language models (LLMs) in tasks such as summarization, argument generation, and judgment prediction. We propose LexChronos, an agentic framework that iteratively extracts structured event timelines from Supreme Court of India judgments. LexChronos employs a dual-agent architecture: a LoRA-instruct-tuned extraction agent identifies candidate events, while a pre-trained feedback agent scores and refines them through a confidence-driven loop. To address the scarcity of Indian legal event datasets, we construct a synthetic corpus of 2000 samples using reverse-engineering techniques with DeepSeek-R1 and GPT-4, generating gold-standard event annotations. Our pipeline achieves a BERT-based F1 score of 0.8751 against this synthetic ground truth. In downstream evaluations on legal text summarization, GPT-4 preferred stru...