Triple
T13657896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaufort |
E326908
|
entity |
| Predicate | fatInDryMatterApprox |
P53132
|
FINISHED |
| Object | around 48 percent |
—
|
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: around 48 percent | Statement: [Beaufort, fatInDryMatterApprox, around 48 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatInDryMatterApprox Context triple: [Beaufort, fatInDryMatterApprox, around 48 percent]
-
A.
typicalFatContent
chosen
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
B.
dryMass
Indicates the mass of an object excluding any contained fluids, propellants, or other consumable materials.
-
C.
milkComposition
Indicates the specific nutrients and components that make up a given sample of milk.
-
D.
fatDistribution
Indicates how body fat is spatially allocated or spread across different regions of an entity.
-
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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc61f0d808190b1cd2a6ba0d930eb |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.