Knowledge-Based Legal Document Assembly
This addresses the need for efficient and interpretable document generation in the legal domain, though it appears incremental as it builds on existing knowledge-based methods.
The paper tackles the problem of automating legal document assembly by developing a system that uses a knowledgebase of formal legal norms and tacit document templates to perform legal reasoning and generate documents, also creating an argument graph for explanation and semantic markup for interoperability.
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 systems in the legal domain.