Triple
T11808691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aubange |
E280813
|
entity |
| Predicate | hasAdministrativeCenter |
P1474
|
FINISHED |
| Object | Aubange (town) |
E280813
|
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: Aubange (town) | Statement: [Aubange, hasAdministrativeCenter, Aubange (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aubange (town) Context triple: [Aubange, hasAdministrativeCenter, Aubange (town)]
-
A.
Aubange
chosen
Aubange is a municipality in the far south of Belgium’s Luxembourg province, known for its proximity to the point where the Belgian, French, and Luxembourgish borders meet.
-
B.
Anguerny
Anguerny is a small commune in the Calvados department of the Normandy region in northwestern France.
-
C.
Aubigny-sur-Nère
Aubigny-sur-Nère is a historic commune in the Cher department of central France, known for its strong Scottish connections and well-preserved medieval architecture.
-
D.
Saint-Aubin
Saint-Aubin is a Burgundy wine village in eastern France known for producing high-quality Chardonnay and Pinot Noir wines, particularly from its premier cru vineyards.
-
E.
Saint-Aubin
Saint-Aubin is a small French commune located in the Île-de-France region, southwest of Paris.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5c93a1881909b428bf3ed55bb57 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131726ab08190ae777bee3ac6df43 |
completed | April 28, 2026, 10:15 p.m. |
Created at: April 8, 2026, 9:42 p.m.