Triple
T20013841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plascassier |
E494658
|
entity |
| Predicate | roadAccessFrom |
P22549
|
FINISHED |
| Object | Grasse |
—
|
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: Grasse | Statement: [Plascassier, roadAccessFrom, Grasse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grasse Context triple: [Plascassier, roadAccessFrom, Grasse]
-
A.
Grasse
chosen
Grasse is a town in southeastern France renowned as the world’s perfume capital and a historic center of the fragrance industry.
-
B.
Aix-en-Provence
Aix-en-Provence is a historic and picturesque city in southern France, renowned for its Provençal charm, fountains, and as the hometown of painter Paul Cézanne.
-
C.
Grasse–Castellane
Grasse–Castellane is a scenic stretch of road in southeastern France that forms part of the historic Route Napoléon through the Alps.
-
D.
Saint-Raphaël
Saint-Raphaël is a coastal resort town on the French Riviera known for its Mediterranean beaches, yacht marina, and scenic Esterel Massif backdrop.
-
E.
Saint-Raphaël
Saint-Raphaël is a commune in northern Haiti known for its agricultural activities and historical significance dating back to the colonial era.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623a9bd48190a3344a07540170c7 |
completed | April 20, 2026, 5:28 p.m. |
Created at: April 11, 2026, 3:34 p.m.