Triple
T2738514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayonne, France |
E60688
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Anglet |
E168470
|
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: Anglet | Statement: [Bayonne, France, nearbyCity, Anglet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anglet Context triple: [Bayonne, France, nearbyCity, Anglet]
-
A.
Anglet
chosen
Anglet is a coastal city in southwestern France, situated between Bayonne and Biarritz in the French Basque Country and known for its Atlantic beaches and surf culture.
-
B.
Villeneuve d’Ascq
Villeneuve d’Ascq is a suburban city in northern France near Lille, known for its universities, technology parks, and modernist urban planning.
-
C.
Boulogne-sur-Mer
Boulogne-sur-Mer is a coastal city and major fishing port in northern France, located on the English Channel in the Pas-de-Calais department.
-
D.
Lorient
Lorient is a port city in the Brittany region of northwestern France, known for its maritime heritage and annual Interceltic Festival.
-
E.
Sète
Sète is a coastal port city in southern France known for its canals, fishing industry, and vibrant maritime culture on the Mediterranean Sea.
- 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_69afbbc607d88190bc35ce56ac26dbf9 |
completed | March 10, 2026, 6:35 a.m. |
Created at: March 6, 2026, 9:56 p.m.