Triple
T3724672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bordeaux wine region |
E81719
|
entity |
| Predicate | hasViticulturalHistorySince |
P12089
|
FINISHED |
| Object | Roman era |
—
|
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: Roman era | Statement: [Bordeaux wine region, hasViticulturalHistorySince, Roman era]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViticulturalHistorySince Context triple: [Bordeaux wine region, hasViticulturalHistorySince, Roman era]
-
A.
viticultureHistory
chosen
Indicates the historical development, practices, and events related to grape cultivation and winemaking over time.
-
B.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
C.
foundedAsVineyard
Indicates that an organization, estate, or property was originally established as a vineyard.
-
D.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcaf54af881908bd8d520595de061 |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc0452f5081909c79e114a86cce8c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.