A Repealed Law Is Not a Stale Fact

Nicolas Figay asked us a question this week that sent us back to read our own source code before we could answer it honestly.

He was making a point about knowledge graphs, and he put a distinction on the table we had never seen stated that cleanly. When a system stores a fact with a time attached, it has quietly made a choice about what kind of thing that fact is. Either it is a property of something that endures, in which case the property can silently rot when the world moves and nobody re-checks. Or it is a temporal part of something extended through time, in which case it never rots at all. It gets superseded by a later part, and the earlier part stays perfectly true of the period it covered.

His observation: most systems never declare which of the two they are in. They attach a timestamp and let you assume.

Where legal text refuses the alternative

Legal text is where that stops being philosophy. You cannot ask a legal corpus for "Article 7". There is no such object. You can only ask for Article 7 as it stood on a particular date, and what comes back carries a window of validity rather than a modification date. Repeal is not decay in that model, it is a boundary between versions. The repealed text was never wrong. It correctly governed the period it governed, and it still does for any question about that period. Which is why in our own system "repealed as of the date consulted" is a verdict in its own right, not an error and not a missing record. We did not choose that out of ontological taste. The domain refused the alternative.

Why this generalizes past law

Here is why it generalizes past law. Most AI systems retrieving from documents carry a timestamp of some kind, and most people reading that field believe it tells them the information is current. It does not. It tells you when someone last touched the record. Those are different questions with different answers, and the gap between them is exactly where confidently wrong output lives. A document indexed this morning can contain a claim that stopped being true two years ago, and nothing in the timestamp will say so.

A point in time is not a primitive

Nicolas pushed further, and this is the part we keep thinking about. A point in time is not a primitive. It is the boundary of an interval with its own internal structure. A fiscal quarter is not a sum of instants. Flattening that structure into a bare timestamp is what makes staleness invisible in the first place.

The interval we do not compute

Which leads somewhere we do not have an answer for yet. If a conclusion rests on two premises, each with its own window of validity, then the conclusion has a window too, and it is the intersection. Premise A held from 2019 to 2023. Premise B has held since 2021. A conclusion built on both was only ever jointly supported for two years, and we may well be standing outside that window right now. That interval is computable. It follows from the parts. And it is not the same thing as checking that each premise is individually current, which is the check most systems would run before calling it done.

We do not compute it. This week we wrote it into the list of declared limitations inside our codebase rather than leaving it as something we knew and had never written down. When we put the question back to Nicolas, he said he is facing the same wall.

That is a better outcome than agreement. Two systems built on entirely different foundations, one a knowledge graph for industrial interoperability and one a citation verifier for legal text, hitting the same unsolved edge from opposite directions. The wall is real, and it sits in a place neither of us had named before the conversation.