Insights on Belgian tax law and AI-powered research
First-stage retrieval finds 100 matches. Reranking identifies the 5 that actually answer your question. Here's why that distinction matters for legal AI.
Keyword search finds exact article numbers. Semantic search finds related concepts. Hybrid search does both — and the difference is measurable.
A search engine finds text. A knowledge graph navigates relationships: which article amends which, which ruling interprets what, which exception overrides the rule. Belgian tax law is a web of cross-references — and a knowledge graph is the map.
Before your legal AI tool can answer a question, it has to cut the law into pieces. The way it cuts determines whether the answer includes the exception that changes everything — or misses it entirely.
A ministerial circular and a Court of Cassation ruling look the same to most AI search systems. That's not a minor flaw — it's a fundamental gap that makes every answer unreliable.
Fine-tuning memorizes yesterday's law. RAG looks up today's. For Belgian tax professionals, this architecture choice determines whether your AI tool is current or confidently outdated.
How retrieval-augmented generation works, why basic RAG still hallucinates, and what a search-RAG fusion architecture adds for tax professionals.
Why language models invent legal citations, what makes Belgian tax especially vulnerable, and three defenses that actually work.