Triple
T21662117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fourme de Montbrison |
E534618
|
entity |
| Predicate | pairingSuggestion |
P93942
|
FINISHED |
| Object | pairs with white wines |
—
|
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: pairs with white wines | Statement: [Fourme de Montbrison, pairingSuggestion, pairs with white wines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pairingSuggestion Context triple: [Fourme de Montbrison, pairingSuggestion, pairs with white wines]
-
A.
starPairing
Indicates a relationship where two stars are associated or grouped together as a pair, typically for observational, analytical, or classificatory purposes.
-
B.
commonPair
Indicates that two entities commonly occur together or are frequently associated as a pair in some shared context.
-
C.
pairsIntroduced
Indicates that one entity has brought together or facilitated the first meeting between two other entities as a pair.
-
D.
isPerfectPairing
chosen
Indicates that two entities complement each other exceptionally well, forming an ideal or highly compatible combination.
-
E.
accompaniesTo
Indicates that one entity goes along with or escorts another entity to a specific destination or event.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0883d481908dfdc66832c34d74 |
completed | April 27, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.