Triple
T244670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Viticultural Area |
E5010
|
entity |
| Predicate | labelingRuleFor |
P6249
|
FINISHED |
| Object | American wine |
—
|
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: American wine | Statement: [American Viticultural Area, labelingRuleFor, American wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelingRuleFor Context triple: [American Viticultural Area, labelingRuleFor, American wine]
-
A.
usesRulesFrom
chosen
Indicates that one entity applies, follows, or is governed by the rules defined or provided by another entity.
-
B.
notableRule
Indicates that a rule or regulation is particularly significant, prominent, or noteworthy within a given context.
-
C.
compositionRule
Indicates how multiple elements or components are combined or arranged according to a specific rule or pattern.
-
D.
nativeLabel
Indicates the label or name of an entity expressed in its own native or original language.
-
E.
recognizedFor
Indicates that one entity is acknowledged, credited, or honored for a particular achievement, quality, contribution, or work associated with another entity.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.