Knowledge-Based Legal Document Assembly
Marko Markovi\'c, Stevan Gostoji\'c

TL;DR
This paper introduces a knowledge-based legal document assembly system that uses formal legal norms and tacit knowledge to generate legal documents, explain reasoning, and enhance interoperability.
Contribution
It presents a novel system combining formal rule-based knowledge and tacit templates for automated legal document assembly with explainability features.
Findings
Developed a proof-of-concept system for legal document assembly.
The system generates interpretable argument graphs explaining reasoning.
Semantic markup facilitates further processing and system interoperability.
Abstract
This paper proposes a knowledge-based legal document assembly method that uses a machine-readable representation of knowledge of legal professionals. This knowledgebase has two components - the formal knowledge of legal norms represented as a rule-base and the tacit knowledge represented by a document template. A document assembly system is developed as a proof of concept. It collects input data in the form of an interactive interview, performs legal reasoning over input data, and generates the output document. The system also creates an argument graph as an explanation of the reasoning process providing the user with an interpretation of how the input data and the rule-base influence the content of the output document. The system also semantically marks up data in the output document, facilitating its further processing and providing support to the interoperability of information…
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Taxonomy
TopicsMulti-Agent Systems and Negotiation · Semantic Web and Ontologies · Topic Modeling
