Triple
T12463434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Cru villages |
E297857
|
entity |
| Predicate | productTypeAssociated |
P62838
|
FINISHED |
| Object | Champagne sparkling 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: Champagne sparkling wine | Statement: [Grand Cru villages, productTypeAssociated, Champagne sparkling wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productTypeAssociated Context triple: [Grand Cru villages, productTypeAssociated, Champagne sparkling wine]
-
A.
componentTypeAssociatedWithBrand
Indicates that a specific component type is linked or affiliated with a particular brand.
-
B.
relatedToProduct
chosen
Indicates a general association or connection between an entity and a specific product, without specifying the exact nature of that relationship.
-
C.
appliesToProductType
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
-
D.
byProduct
Indicates that one entity is produced incidentally or as a secondary result of a process, activity, or creation involving another entity.
-
E.
vendorProductOf
Indicates that a product is offered or supplied by a particular vendor.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.