Triple
T28265450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dealu Mare wine region |
E712689
|
entity |
| Predicate | wineColorSpecialty |
P12088
|
FINISHED |
| Object | red |
—
|
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: red | Statement: [Dealu Mare wine region, wineColorSpecialty, red]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineColorSpecialty Context triple: [Dealu Mare wine region, wineColorSpecialty, red]
-
A.
wineColor
chosen
Indicates the color attribute or hue associated with a given wine.
-
B.
wineSpeciality
Indicates that an entity (such as a person, place, or establishment) is particularly known for, focused on, or distinguished by a specific type or aspect of wine.
-
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.
wineColorMajority
Indicates that the majority of a given set or collection of wines share the same color.
-
E.
wineCategory
Indicates the classification or type of wine that an entity (such as a specific wine) belongs to.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6441d0e5c8190ba32a2107c3f368a |
completed | May 2, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:14 p.m.