Triple
T5179848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nantes Atlantique Airport |
E116892
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bouguenais |
E393203
|
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: Bouguenais | Statement: [Nantes Atlantique Airport, locatedIn, Bouguenais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bouguenais Context triple: [Nantes Atlantique Airport, locatedIn, Bouguenais]
-
A.
Bouguenais
chosen
Bouguenais is a suburban commune in western France, located near Nantes and known for hosting Nantes Atlantique Airport.
-
B.
Pontgouin
Pontgouin is a small commune in northern France’s Eure-et-Loir department, known for its rural setting and the Eure River running through it.
-
C.
Vieux-Bassin
Vieux-Bassin is the picturesque old harbor of Honfleur in Normandy, France, renowned for its historic slate-fronted houses and artistic heritage.
-
D.
Golfe-Juan
Golfe-Juan is a seaside district on the French Riviera, known for its beaches and marina on the Mediterranean coast.
-
E.
Aigues-Mortais
Aigues-Mortais are the inhabitants of Aigues-Mortes, a historic fortified town in the Occitanie region of southern France.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79978a208190b2e5909795108327 |
completed | March 20, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed9553bc0819082a37a83a3edf7e8 |
completed | March 21, 2026, 5:45 p.m. |
Created at: March 20, 2026, 1:45 p.m.