Triple
T3261134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiambalá |
E68410
|
entity |
| Predicate | hasTypeOfVineyards |
P27084
|
FINISHED |
| Object | high-altitude vineyards |
—
|
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: high-altitude vineyards | Statement: [Fiambalá, hasTypeOfVineyards, high-altitude vineyards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfVineyards Context triple: [Fiambalá, hasTypeOfVineyards, high-altitude vineyards]
-
A.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
B.
viticulturalAreaType
chosen
Indicates the specific type or classification of a viticultural area associated with an entity.
-
C.
hasWinery
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
D.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
E.
viticulturalCharacteristic
Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafa7fea08190b089b6174fd7cd32 |
completed | March 8, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69ada41d7eac8190ada4bf5f793d5c49 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.