Workflow
Knowledge Graph in Legal
Definition
A legal knowledge graph is a structured representation of relationships between legal concepts, authorities, entities, and documents. It maps how cases cite each other, how statutes relate to regulations, how legal concepts connect across practice areas, and how a firm's work product relates to specific legal issues, enabling the AI to understand law as an interconnected system rather than isolated documents.
Law is fundamentally a system of interconnected authorities and concepts. Cases cite other cases, statutes are interpreted by regulations, legal doctrines evolve through chains of opinions, and practice areas overlap in complex ways. A knowledge graph captures these relationships in a structured format that AI systems can traverse and reason about.
In legal AI applications, knowledge graphs enable several powerful capabilities. They allow the system to follow citation chains to identify the most authoritative treatment of a legal issue. They reveal connections between seemingly unrelated areas of law that share underlying principles. They map the evolution of legal doctrine, showing how a rule has been interpreted, narrowed, or expanded over time. And they connect a firm's internal work product to the broader legal landscape.
The construction of legal knowledge graphs requires significant domain expertise. Legal relationships are nuanced: a case might distinguish rather than overrule a prior opinion, a statute might preempt state law in some circumstances but not others, and a regulatory interpretation might apply only to specific fact patterns. Effective legal knowledge graphs capture these nuances, providing AI systems with a rich understanding of legal structure that improves every downstream task from research to drafting.
How Irys approaches this
Irys leverages knowledge graph technology to understand relationships between legal authorities, enabling more contextual research results and more accurate cross-referencing across the legal landscape.
Related terms
AI Concepts
Semantic Search in Legal
Semantic search is a search methodology that understands the meaning and intent behind a query rather than matching exact keywords. In legal research, semantic search allows lawyers to describe a legal issue in natural language and find relevant cases, statutes, and secondary sources even when they use different terminology than the query.
Legal Tech
Legal Knowledge Management
Legal knowledge management is the systematic process of capturing, organizing, and making accessible the collective expertise and work product of a legal organization. AI-enhanced knowledge management goes beyond document storage to understand the substance of legal work, automatically categorize materials, and surface relevant precedents when lawyers need them.
Research
Citation Verification
Citation verification is the process of independently confirming that the legal citations in a document hold up: that the cited authorities exist, that quoted language matches the source, and that the authorities have not been overruled or negatively treated. In AI-assisted legal work it is the step that catches hallucinated or inaccurate references, and it supports the reviewing attorney's own verification duty rather than replacing it.
Legal Tech
AI Legal Research
AI legal research uses artificial intelligence to find, analyze, and synthesize legal authorities including case law, statutes, regulations, and secondary sources. Unlike traditional database searches that return ranked lists of documents, AI legal research can answer natural language questions, provide analytical summaries, and identify relevant authorities that keyword searches would miss.
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