Triple
T1856452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayonne |
E41714
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Sète |
E157839
|
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: Sète | Statement: [Bayonne, twinTown, Sète]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sète Context triple: [Bayonne, twinTown, Sète]
-
A.
Sète
chosen
Sète is a coastal port city in southern France known for its canals, fishing industry, and vibrant maritime culture on the Mediterranean Sea.
-
B.
La Grande-Motte
La Grande-Motte is a seaside resort town on France’s Mediterranean coast, noted for its distinctive modernist pyramid-shaped architecture and beaches.
-
C.
Perpignan
Perpignan is a historic city in southern France near the Spanish border, known for its Catalan culture and Mediterranean climate.
-
D.
Béziers
Béziers is a historic city in southern France known for its wine production, ancient Roman heritage, and the famous Feria de Béziers festival.
-
E.
Blaye
Blaye is a wine-producing area on the right bank of the Gironde estuary in southwestern France, known for its red and white Bordeaux wines and historic citadel.
- 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb07e5ed48190a7b8858e2b355109 |
completed | March 7, 2026, 4:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae95e5cf008190a6638bb2c8d4d505 |
completed | March 9, 2026, 9:41 a.m. |
Created at: March 4, 2026, 7:33 p.m.