Triple
T30312761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chicken tempura (toriten) |
E770969
|
entity |
| Predicate | oilUsedForFrying |
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: [chicken tempura (toriten), oilUsedForFrying, vegetable oil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oilUsedForFrying Context triple: [chicken tempura (toriten), oilUsedForFrying, vegetable oil]
-
A.
fryCook
Indicates that one entity works as a cook who prepares food by frying, typically in a restaurant or similar setting, for another entity (such as an employer or establishment).
-
B.
oilContent
Indicates the amount or proportion of oil present in a given substance, material, or item.
-
C.
oilType
chosen
Indicates the specific kind or classification of oil associated with an entity.
-
D.
oilUsage
Indicates the amount or pattern of oil consumed or utilized by an entity over a given context or period.
-
E.
cookingFuel
Indicates that one entity serves as the fuel or energy source used by another entity for cooking activities.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6816ceb688190b2e5f01205f3c550 |
completed | May 2, 2026, 10:57 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:50 p.m.