Triple
T4307647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sulguni cheese |
E93993
|
entity |
| Predicate | fatContent |
P53132
|
FINISHED |
| Object | medium to high |
—
|
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: medium to high | Statement: [sulguni cheese, fatContent, medium to high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatContent Context triple: [sulguni cheese, fatContent, medium to high]
-
A.
typicalFatContent
chosen
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
B.
fattyAcid
Indicates a relationship where one entity is a fatty acid component, derivative, or participant in a process involving another entity.
-
C.
typicalFatUsed
Indicates that a particular type of fat is commonly or characteristically used in a given context or application.
-
D.
diet
Indicates that an entity regularly consumes a particular type or range of food as its primary source of nutrition.
-
E.
oilContent
Indicates the amount or proportion of oil present in a given substance, material, or item.
- 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_69b3451886588190a3dd1305ea7c58dc |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b350d2af088190ad7cb035d6e0f8c2 |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b34f4a07b08190a06ada0d9cbb14fb |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:11 p.m.