Triple
T29467424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Churchkhela |
E747416
|
entity |
| Predicate | typicalNut |
P62846
|
FINISHED |
| Object | walnut |
—
|
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: walnut | Statement: [Churchkhela, typicalNut, walnut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNut Context triple: [Churchkhela, typicalNut, walnut]
-
A.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
B.
nutritionStandard
Indicates that something complies with, or is evaluated against, a defined set of nutritional guidelines or requirements.
-
C.
commonNut
Indicates that two or more entities share the same type of nut or are associated with an identical nut component.
-
D.
nutritionComponent
chosen
Indicates that one entity is a nutritional constituent, ingredient, or component of another (typically a food, diet, or nutritional product).
-
E.
typicalFatContent
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
- 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_69f0bd42cf308190bb01b20bc5b7c2d0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a01ca0db6f08190bed479584114e63d |
completed | May 11, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_6a01c96ff4a08190a4fbf0cebbda95b4 |
completed | May 11, 2026, 12:20 p.m. |
Created at: April 28, 2026, 3:54 p.m.