Triple
T14930638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentière |
E372252
|
entity |
| Predicate | hasNearbyPeak |
P7612
|
FINISHED |
| Object | Les Courtes |
E1059847
|
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: Les Courtes | Statement: [Argentière, hasNearbyPeak, Les Courtes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Courtes Context triple: [Argentière, hasNearbyPeak, Les Courtes]
-
A.
Les Courtes
chosen
Les Courtes is a prominent peak in the Mont Blanc massif of the French Alps, known for its steep faces and classic alpine climbing routes.
-
B.
Les Courtilles
Les Courtilles is a Paris Métro station that serves as one of the termini of Line 13 in the northwestern suburbs of the city.
-
C.
Calvaises
Calvaises are the inhabitants or natives of the town of Calvi, typically referring to its local population and community.
-
D.
Le Roeulx
Le Roeulx is a historic town in the province of Hainaut in Wallonia, Belgium, known for its castle, traditional architecture, and proximity to the Canal du Centre.
-
E.
Le Brusquet
Le Brusquet is a small commune in southeastern France situated in the Alpes-de-Haute-Provence department.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64550dc8190ba44120df00ba498 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72c728948190a1cfc62f4038b6ec |
completed | May 8, 2026, 11:33 p.m. |
Created at: April 10, 2026, 2:36 a.m.