Triple
T30143497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sant Esteve Sesrovires |
E766188
|
entity |
| Predicate | hasWineGrowingLandscape |
P25137
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Sant Esteve Sesrovires, hasWineGrowingLandscape, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineGrowingLandscape Context triple: [Sant Esteve Sesrovires, hasWineGrowingLandscape, true]
-
A.
hasVineyards
chosen
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
B.
hasVineyardsNear
Indicates that one entity possesses or is associated with vineyards located in close geographic proximity to another entity.
-
C.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
D.
hasWinery
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
E.
producesWine
Indicates that one entity creates or manufactures wine as a product.
- F. None of above.
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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 29, 2026, 7:18 p.m.