Triple
T16290616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lledoner Pelut |
E395510
|
entity |
| Predicate | viticulturalTrait |
P42963
|
FINISHED |
| Object | good color extraction |
—
|
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: good color extraction | Statement: [Lledoner Pelut, viticulturalTrait, good color extraction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viticulturalTrait Context triple: [Lledoner Pelut, viticulturalTrait, good color extraction]
-
A.
viticulturalCharacteristic
Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
-
B.
viticulturalFeature
chosen
Indicates a characteristic, condition, or attribute specifically related to grape growing or vineyard cultivation.
-
C.
viticulturalFocus
Indicates a focus on or specialization in viticulture, i.e., activities, practices, or interests centered on grape growing and vineyard management.
-
D.
viticulturePractice
Indicates a relationship where a specific method, technique, or practice is used in the cultivation and management of grapevines.
-
E.
wineGrapesCultivated
Indicates that certain grape varieties are grown or cultivated specifically for producing wine.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2491821d0819086cffdd7551ba85a |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.