Triple
T7143419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château d’Azay-le-Rideau |
E166505
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Azay-le-Rideau |
E317880
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Azay-le-Rideau | Statement: [Château d’Azay-le-Rideau, locatedIn, Azay-le-Rideau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azay-le-Rideau Context triple: [Château d’Azay-le-Rideau, locatedIn, Azay-le-Rideau]
-
A.
Azay-le-Rideau
chosen
Azay-le-Rideau is a picturesque commune in central France best known for its Renaissance château set on an island in the Indre River.
-
B.
Trois-Ponts
Trois-Ponts is a small municipality in the province of Liège in Wallonia, Belgium, known for its scenic Ardennes landscape and railway junction.
-
C.
Oyonnax
Oyonnax is a town in eastern France’s Ain department, known historically for its plastics industry and its role in the French Resistance during World War II.
-
D.
Bourgueil
Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
-
E.
Butte-aux-Cailles
Butte-aux-Cailles is a picturesque, village-like neighborhood in Paris known for its cobbled streets, street art, and lively cafés.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7d027d0819088598b2a9f71b1b7 |
completed | March 27, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ad98576481908b8b82f675079fca |
completed | March 28, 2026, 10:29 a.m. |
Created at: March 27, 2026, 2:46 p.m.