Triple
T27916460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooking at El Diablo restaurant |
E706087
|
entity |
| Predicate | cooksFood |
P61222
|
FINISHED |
| Object | over geothermal heat |
—
|
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: over geothermal heat | Statement: [Cooking at El Diablo restaurant, cooksFood, over geothermal heat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cooksFood Context triple: [Cooking at El Diablo restaurant, cooksFood, over geothermal heat]
-
A.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
B.
cooksSimilarTo
Indicates that one entity prepares or cooks food in a way that is similar to how another entity does.
-
C.
isUsuallyCookedIn
chosen
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
D.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
E.
recipe
Indicates that one entity is a set of instructions or method used to create, prepare, or produce 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_69ef96b6cc808190aab19fb18b235f4b |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 6:54 p.m.