Triple
T6094089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Eutrope |
E135834
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Charente-Maritime |
E257427
|
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: Charente-Maritime | Statement: [Saint Eutrope, associatedWith, Charente-Maritime]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charente-Maritime Context triple: [Saint Eutrope, associatedWith, Charente-Maritime]
-
A.
Charente-Maritime
chosen
Charente-Maritime is a coastal department in southwestern France known for its Atlantic shoreline, islands, and maritime heritage.
-
B.
Mayenne
Mayenne is a department in northwestern France known for its rural landscapes, historic towns, and location within the former province of Maine.
-
C.
Mayenne
Mayenne is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
-
D.
Maine-et-Loire
Maine-et-Loire is a department in western France known for its historic towns, châteaux, and vineyards along the Loire River.
-
E.
Tarn-et-Garonne
Tarn-et-Garonne is a department in the Occitanie region of southern France, known for its agricultural landscapes, historic towns, and location along the Garonne and Tarn rivers.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05a9516ec819093e94ee8d3244e1b |
completed | March 22, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1253b2cb48190be682e9184cf4f5d |
completed | March 23, 2026, 11:34 a.m. |
Created at: March 22, 2026, 4:12 p.m.