Triple
T17600496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argelès-Gazost |
E428686
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Cauterets |
—
|
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: Cauterets | Statement: [Argelès-Gazost, near, Cauterets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cauterets Context triple: [Argelès-Gazost, near, Cauterets]
-
A.
Cauterets
chosen
Cauterets is a spa and ski resort town in the French Pyrenees known for its thermal baths, mountain scenery, and access to popular hiking areas.
-
B.
Aurillac
Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
-
C.
Ussel
Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
-
D.
Montauroux
Montauroux is a picturesque commune in southeastern France’s Var department, known for its hilltop setting overlooking the Pays de Fayence and proximity to the French Riviera.
-
E.
Mazamet
Mazamet is a town in southern France known historically for its wool and leather industries, situated in the Tarn department within the Occitanie region.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4812d48190bf8e899fa8f7fbe4 |
completed | April 19, 2026, 5:46 a.m. |
Created at: April 10, 2026, 5:51 a.m.