Triple
T2958036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanc Fumé |
E79978
|
entity |
| Predicate | labelingContext |
P34621
|
FINISHED |
| Object | style-indicative name for Sauvignon Blanc |
—
|
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: style-indicative name for Sauvignon Blanc | Statement: [Blanc Fumé, labelingContext, style-indicative name for Sauvignon Blanc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelingContext Context triple: [Blanc Fumé, labelingContext, style-indicative name for Sauvignon Blanc]
-
A.
canonicalContext
Indicates the standard or primary contextual framework within which an entity, statement, or resource is to be interpreted.
-
B.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
C.
contextOf
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
D.
namedInContextOf
chosen
Indicates that an entity is mentioned or identified specifically within a particular context, situation, or frame of reference.
-
E.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992b33e081909d22a19d5064c47d |
completed | March 8, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.