Triple
T18580116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agde station |
E454088
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Cap d’Agde |
—
|
NE NERFINISHED |
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: Cap d’Agde | Statement: [Agde station, locatedNear, Cap d’Agde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cap d’Agde Context triple: [Agde station, locatedNear, Cap d’Agde]
-
A.
Cap d’Agde
chosen
Cap d’Agde is a Mediterranean seaside resort town in southern France, famous for its extensive beaches and large naturist village.
-
B.
Leucate
Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
-
C.
Argelès-sur-Mer
Argelès-sur-Mer is a coastal resort town in southern France known for its long Mediterranean beaches and proximity to the Pyrenees.
-
D.
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.
-
E.
Gardanne
Gardanne is a commune in southern France known for its industrial heritage and location between Marseille and Aix-en-Provence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543cf33288190bc2cd6b7befde944 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 11:43 a.m.