Triple
T13612039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ossau Valley |
E325213
|
entity |
| Predicate | hasSkiResort |
P1981
|
FINISHED |
| Object | Gourette |
E303995
|
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: Gourette | Statement: [Ossau Valley, hasSkiResort, Gourette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gourette Context triple: [Ossau Valley, hasSkiResort, Gourette]
-
A.
Gourette
chosen
Gourette is a French mountain ski resort village in the Pyrenees, known for its alpine slopes and scenic high-altitude setting.
-
B.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
-
C.
Duguay-Trouin
Duguay-Trouin was a French warship that served in the early 19th century, notably participating in the Napoleonic naval conflicts.
-
D.
Barbaroux
Barbaroux is a French surname most notably associated with Charles Barbaroux, a prominent figure of the French Revolution.
-
E.
Perros-Guirec
Perros-Guirec is a coastal resort town in Brittany, France, renowned for its Pink Granite Coast, beaches, and scenic seaside landscapes.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0aa9a1481908c6f92495aff86c6 |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f9a9f9c81909b0a8f4f51c461ae |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:50 p.m.