Triple
T2738502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayonne, France |
E60688
|
entity |
| Predicate | hasHeritageSite |
P923
|
FINISHED |
| Object | Château-Neuf |
E217674
|
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: Château-Neuf | Statement: [Bayonne, France, hasHeritageSite, Château-Neuf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Château-Neuf Context triple: [Bayonne, France, hasHeritageSite, Château-Neuf]
-
A.
Château-Neuf
chosen
Château-Neuf is a historic fortress in Bayonne, France, that once formed part of the city’s defensive stronghold along the Adour River.
-
B.
Château-Vieux
Château-Vieux is a historic medieval fortress in Bayonne, France, notable for its long military and architectural heritage.
-
C.
Castelroussin
Castelroussin is the French demonym for an inhabitant of the city of Châteauroux in central France.
-
D.
Château Olivier
Château Olivier is a historic Bordeaux wine estate in the Pessac-Léognan appellation, renowned for producing both red and white grand cru classé wines.
-
E.
Châtel-Guyon
Châtel-Guyon is a French spa town in the Auvergne region, known for its thermal springs and Belle Époque architecture.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb147a588190829b74fe05b3a114 |
completed | March 7, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc039a9988190a01036b15a19be6c |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 6, 2026, 9:56 p.m.