Triple
T21662101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fourme de Montbrison |
E534618
|
entity |
| Predicate | fatContentApproximate |
P53132
|
FINISHED |
| Object | 50% of dry matter |
—
|
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: 50% of dry matter | Statement: [Fourme de Montbrison, fatContentApproximate, 50% of dry matter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatContentApproximate Context triple: [Fourme de Montbrison, fatContentApproximate, 50% of dry matter]
-
A.
typicalFatContent
chosen
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
B.
fatDistribution
Indicates how body fat is spatially allocated or spread across different regions of an entity.
-
C.
fatStorage
Indicates the process or state in which an organism or system accumulates and retains fat as an energy reserve.
-
D.
fatColor
Indicates the color characteristic associated with an entity’s fat or fatty tissue.
-
E.
fattyAcid
Indicates a relationship where one entity is a fatty acid component, derivative, or participant in a process involving 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_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.