Triple
T34225970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alella |
E878045
|
entity |
| Predicate | isWineProducingTown |
P178705
|
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: [Alella, isWineProducingTown, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWineProducingTown Context triple: [Alella, isWineProducingTown, true]
-
A.
producesWine
Indicates that one entity creates or manufactures wine as a product.
-
B.
alsoProducesWineIn
Indicates that the subject, in addition to other products or activities, produces wine in the specified location or context.
-
C.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
D.
isWineCapitalOf
Indicates that a place is recognized as the primary center or leading hub for wine production, trade, or culture for a specified region or category.
-
E.
hasLargestWinegrowingCommune
Indicates that one entity possesses or contains the largest winegrowing commune in comparison to other relevant entities.
- F. None of above. chosen
Provenance (4 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_69f349b16d0481908754e3069f05e0c1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f713bfdc148190a249a7874320bab8 |
completed | May 3, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f7135fa2988190a20a94cfe616d754 |
completed | May 3, 2026, 9:20 a.m. |
Created at: May 1, 2026, 1:55 a.m.