Triple
T18387861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tarte flambée |
E446638
|
entity |
| Predicate | traditionalCookingTemperature |
P10567
|
FINISHED |
| Object | very high 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: very high heat | Statement: [tarte flambée, traditionalCookingTemperature, very high heat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalCookingTemperature Context triple: [tarte flambée, traditionalCookingTemperature, very high heat]
-
A.
requiresCookingTemperature
chosen
Indicates that performing the action or preparing the item necessitates reaching or maintaining a specific cooking temperature.
-
B.
typicalCookingTime
Indicates the usual duration required to cook something under standard or commonly accepted conditions.
-
C.
brewingTemperature
Indicates the specific temperature at which a brewing process is carried out.
-
D.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
E.
heatingMethod
Indicates the method or technique used to apply heat to something, such as for cooking, warming, or processing.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e517a114c08190af1be1ae52c83b63 |
completed | April 19, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:46 a.m.