Triple
T15181439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loup |
E362753
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | La Colle-sur-Loup |
E794178
|
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: La Colle-sur-Loup | Statement: [Loup, flowsThrough, La Colle-sur-Loup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Colle-sur-Loup Context triple: [Loup, flowsThrough, La Colle-sur-Loup]
-
A.
La Colle-sur-Loup
chosen
La Colle-sur-Loup is a picturesque Provençal village in southeastern France, known for its historic charm and location near the French Riviera.
-
B.
Casseneuil
Casseneuil is a small commune in southwestern France, located in the Lot-et-Garonne department in the Nouvelle-Aquitaine region.
-
C.
Celles-sur-Durolle
Celles-sur-Durolle is a commune in central France’s Puy-de-Dôme department, known historically for its cutlery and metalworking industries along the Durolle River.
-
D.
Vaujours
Vaujours is a small suburban commune in the northeastern outskirts of Paris, France.
-
E.
Brière
Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006663ad48190986b680001be0e9b |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffee31b70819092d0583100a7101a |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 3:09 a.m.