Triple
T24909041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haro |
E623793
|
entity |
| Predicate | wineDenomination |
P157224
|
FINISHED |
| Object | DOCa Rioja |
—
|
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: DOCa Rioja | Statement: [Haro, wineDenomination, DOCa Rioja]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineDenomination Context triple: [Haro, wineDenomination, DOCa Rioja]
-
A.
wineCategory
Indicates the classification or type of wine that an entity (such as a specific wine) belongs to.
-
B.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
C.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
D.
wineLaw
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
-
E.
wineComponent
Indicates that one entity is a constituent ingredient or part of a wine represented by the other entity.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f4236db55c8190a1c55a0db86562d8 |
completed | May 1, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f423637bec8190a1701421ac86a3b7 |
completed | May 1, 2026, 3:52 a.m. |
Created at: April 18, 2026, 5:27 a.m.