Triple
T23760198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet and Sour Carp |
E587227
|
entity |
| Predicate | typicalCookingOil |
P13240
|
FINISHED |
| Object | vegetable oil |
—
|
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: vegetable oil | Statement: [Sweet and Sour Carp, typicalCookingOil, vegetable oil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCookingOil Context triple: [Sweet and Sour Carp, typicalCookingOil, vegetable oil]
-
A.
oilType
chosen
Indicates the specific kind or classification of oil associated with an entity.
-
B.
oilContent
Indicates the amount or proportion of oil present in a given substance, material, or item.
-
C.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
D.
typicalFatContent
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
E.
typicalSpices
Indicates that certain spices are commonly or characteristically used in association with a particular dish, cuisine, or ingredient.
- 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_69e2490b8ac48190a6b35f1d5500486b |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bdb1d6348190afb3f0fbea1b9ca3 |
completed | April 29, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:14 p.m.