LexDrafter: Terminology Drafting for Legislative Documents using Retrieval Augmented Generation
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Abstract (arXiv)
With the increase in legislative documents at the EU, the number of new terms and their definitions is increasing as well. As per the Joint Practical Guide of the European Parliament, the Council and the Commission, terms used in legal documents shall be consistent, and identical concepts shall be expressed without departing from their meaning in ordinary, legal, or technical language. Thus, while drafting a new legislative document, having a framework that provides insights about existing definitions and helps define new terms based on a document's context will support such harmonized legal definitions across different regulations and thus avoid ambiguities. In this paper, we present LexDrafter, a framework that assists in drafting Definitions articles for legislative documents using retrieval augmented generation (RAG) and existing term definitions present in different legislative documents. For this, definition elements are built by extracting definitions from existing documents. Using definition elements and RAG, a Definitions article can be suggested on demand for a legislative document that is being drafted. We demonstrate and evaluate the functionality of LexDrafter using a collection of EU documents from the energy domain. The code for LexDrafter framework is available at https://github.com/achouhan93/LexDrafter.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 13 of its 33 references that are in the map. First posted on arXiv 24 Mar 2024.
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13 of 33 references.
References · 13
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Citing papers per year: 2024: 1; 2025: 5.
6 papers.
- 2024Studying Large Language Model Behaviors Under Context-Memory Conflicts With Real Documentscited by 27
- 2025Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoningcited by 13
- 2025LegalRAG: A Hybrid RAG System for Multilingual Legal Information Retrievalcited by 5
- 2025REIS: A High-Performance and Energy-Efficient Retrieval System with In-Storage Processingcited by 4
- 2025From Answers to Guidance: A Proactive Dialogue System for Legal Documentscited by 1
- 2025Comparing the Performance of LLMs in RAG-based Question-Answering: A Case Study in Computer Science Literaturecited by 0
- 2025Comparing the Performance of LLMs in RAG-based Question-Answering: A Case Study in Computer Science Literature5 Nov 2025
- 2025From Answers to Guidance: A Proactive Dialogue System for Legal Documents22 Oct 2025
- 2025REIS: A High-Performance and Energy-Efficient Retrieval System with In-Storage Processing19 Jun 2025
- 2025LegalRAG: A Hybrid RAG System for Multilingual Legal Information Retrieval19 Apr 2025
- 2025Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning11 Feb 2025
- 2024Studying Large Language Model Behaviors Under Context-Memory Conflicts With Real Documents24 Apr 2024
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