Triple
T21662112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fourme de Montbrison |
E534618
|
entity |
| Predicate | typicalDiameterRange |
P48665
|
FINISHED |
| Object | 13 to 16 cm |
—
|
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: 13 to 16 cm | Statement: [Fourme de Montbrison, typicalDiameterRange, 13 to 16 cm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDiameterRange Context triple: [Fourme de Montbrison, typicalDiameterRange, 13 to 16 cm]
-
A.
typicalCaseDiameter
chosen
Indicates the usual or standard diameter value associated with an object or case in typical conditions.
-
B.
typicalMassRange
Indicates the usual or expected range of mass values associated with an entity.
-
C.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
D.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
E.
bodyDiameter
Indicates the measurement of how wide an object's body is across its broadest cross-section.
- 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.