Triple
T30197446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacherenc-du-Vic-Bilh |
E767672
|
entity |
| Predicate | sweetStyleLabel |
P169366
|
FINISHED |
| Object | Pacherenc-du-Vic-Bilh doux |
—
|
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: Pacherenc-du-Vic-Bilh doux | Statement: [Pacherenc-du-Vic-Bilh, sweetStyleLabel, Pacherenc-du-Vic-Bilh doux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sweetStyleLabel Context triple: [Pacherenc-du-Vic-Bilh, sweetStyleLabel, Pacherenc-du-Vic-Bilh doux]
-
A.
fashionLabel
Indicates that an entity is a fashion brand or label associated with the design, production, or marketing of clothing or accessories.
-
B.
fashionLabelType
Indicates the specific category or type of fashion label associated with an item or brand.
-
C.
styleCategory
Indicates the stylistic classification or genre category that an item, work, or entity belongs to.
-
D.
styleDetail
Indicates a relationship where specific stylistic characteristics or attributes of something are described or specified in detail.
-
E.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67fc237608190b6542b56038a7fe4 |
completed | May 2, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 29, 2026, 7:30 p.m.