Triple
T71707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chardonnay |
E1433
|
entity |
| Predicate | notableRegionStyle |
P22
|
FINISHED |
| Object | Chablis-style lean and mineral |
—
|
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: Chablis-style lean and mineral | Statement: [Chardonnay, notableRegionStyle, Chablis-style lean and mineral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRegionStyle Context triple: [Chardonnay, notableRegionStyle, Chablis-style lean and mineral]
-
A.
notableStandard
Indicates that one entity is a widely recognized or influential standard that the other entity is associated with or exemplifies.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
notableRule
Indicates that a rule or regulation is particularly significant, prominent, or noteworthy within a given context.
-
D.
notableFor
chosen
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
E.
regionName
Indicates the name assigned to a specific geographic or administrative region.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.