RATIO: A Graph-Aware Framework for Precedent-Grounded Legal Retrieval
RATIO: A Graph-Aware Framework for Precedent-Grounded Legal Retrieval
A graph-aware retrieval framework for legal precedent search that explicitly models the citation network of Nigerian case law rather than relying solely on semantic similarity. Includes the first open citation graph for Nigerian case law (14,437 judgments, 51,465 typed citation edges), a binding horizon filter operationalising temporal validity and jurisdictional binding as executable graph masks, and a trained Graph Attention Network for authority-aware retrieval re-ranking.
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legal retrieval, citation graph, African NLP, knowledge graphs, graph neural networks, legal RAG, legal hallucination, graph attention networks, precedent retrieval, Nigerian law
legal retrieval, citation graph, African NLP, knowledge graphs, graph neural networks, legal RAG, legal hallucination, graph attention networks, precedent retrieval, Nigerian law
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
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