Extract-Explain-Abstract: A Rhetorical Role-Driven Domain-Specific Summarisation Framework for Indian Legal Documents

Veer Chheda, Aaditya Uday Ghaisas, Avantika Sankhe, Dr. Narendra Shekokar


Abstract
Legal documents are characterized by theirlength, intricacy, and dense use of jargon, making efficacious summarisation both paramountand challenging. Existing zero-shot methodologies in small language models struggle tosimplify this jargon and are prone to punts andhallucinations with longer prompts. This paperintroduces the Rhetorical Role-based Extract-Explain-Abstract (EEA) Framework, a novelthree-stage methodology for summarisation ofIndian legal documents in low-resource settings. The approach begins by segmenting legaltexts using rhetorical roles, such as facts, issues and arguments, through a domain-specificphrase corpus and extraction based on TF-IDF.In the explanation stage, the segmented output is enriched with logical connections to ensure coherence and legal fidelity. The final abstraction phase condenses these interlinked segments into cogent, high-level summaries thatpreserve critical legal reasoning. Experimentson Indian legal datasets show that the EEAframework typically outperforms in ROUGE,BERTScore, Flesch Reading Ease, Age of Acquisition, SummaC and human evaluations. Wealso employ InLegalBERTScore as a metric tocapture domain specific semantics of Indianlegal documents.
Anthology ID:
2025.nllp-1.32
Volume:
Proceedings of the Natural Legal Language Processing Workshop 2025
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Nikolaos Aletras, Ilias Chalkidis, Leslie Barrett, Cătălina Goanță, Daniel Preoțiuc-Pietro, Gerasimos Spanakis
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NLLP | WS
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Publisher:
Association for Computational Linguistics
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Pages:
439–455
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https://preview.aclanthology.org/ingest-emnlp/2025.nllp-1.32/
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Cite (ACL):
Veer Chheda, Aaditya Uday Ghaisas, Avantika Sankhe, and Dr. Narendra Shekokar. 2025. Extract-Explain-Abstract: A Rhetorical Role-Driven Domain-Specific Summarisation Framework for Indian Legal Documents. In Proceedings of the Natural Legal Language Processing Workshop 2025, pages 439–455, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
Extract-Explain-Abstract: A Rhetorical Role-Driven Domain-Specific Summarisation Framework for Indian Legal Documents (Chheda et al., NLLP 2025)
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https://preview.aclanthology.org/ingest-emnlp/2025.nllp-1.32.pdf