Triple
T15860357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chantilly, France |
E384565
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Gouvieux |
E909811
|
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: Gouvieux | Statement: [Chantilly, France, near, Gouvieux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gouvieux Context triple: [Chantilly, France, near, Gouvieux]
-
A.
Gouvieux
chosen
Gouvieux is a commune in northern France known for hosting the French residence of Aga Khan IV, Shah Karim al-Husayni.
-
B.
Sury-en-Vaux
Sury-en-Vaux is a small rural commune in the Cher department of central France, known for its vineyards and traditional countryside setting.
-
C.
Bourmont
Bourmont is a historic hilltop town in northeastern France known for its medieval architecture and panoramic views over the surrounding Haute-Marne countryside.
-
D.
Fauvillers
Fauvillers is a rural municipality in the province of Luxembourg in Wallonia, Belgium, known for its small villages and countryside landscapes.
-
E.
Escoutoux
Escoutoux is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555a1f008190bb3f03b0f35ed8a4 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000777c6a08190a4deed9952179be5 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 4:50 a.m.