Triple
T3882824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | boeuf bourguignon |
E92863
|
entity |
| Predicate | usesWineType |
P52137
|
FINISHED |
| Object | Burgundy 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: Burgundy wine | Statement: [boeuf bourguignon, usesWineType, Burgundy wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWineType Context triple: [boeuf bourguignon, usesWineType, Burgundy wine]
-
A.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
-
B.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
C.
producesWine
Indicates that one entity creates or manufactures wine as a product.
-
D.
whiteWineProductionAllowed
Indicates that producing white wine is permitted under the relevant rules, regulations, or conditions.
-
E.
grapeVarietyAllowed
Indicates that a specific grape variety is permitted or authorized for use in a given context, such as a wine, region, or product specification.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.