Triple
T27916447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Diablo restaurant |
E706086
|
entity |
| Predicate | cookingSurfaceTemperature |
P4459
|
FINISHED |
| Object | high temperature from geothermal vents |
—
|
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: high temperature from geothermal vents | Statement: [El Diablo restaurant, cookingSurfaceTemperature, high temperature from geothermal vents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cookingSurfaceTemperature Context triple: [El Diablo restaurant, cookingSurfaceTemperature, high temperature from geothermal vents]
-
A.
cookingSurface
Indicates that one entity serves as the surface or area on which another entity is used for cooking.
-
B.
bakingSurface
Indicates that one entity serves as the surface or platform on which another entity is baked.
-
C.
requiresCookingTemperature
Indicates that performing the action or preparing the item necessitates reaching or maintaining a specific cooking temperature.
-
D.
heatingMethod
Indicates the method or technique used to apply heat to something, such as for cooking, warming, or processing.
-
E.
hasTemperature
chosen
Indicates that an entity possesses or is characterized by a specific temperature value.
- 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.