Triple
T6997929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parmigiano Reggiano |
E162263
|
entity |
| Predicate | cookingTemperature |
P10567
|
FINISHED |
| Object | high-temperature cooked curd |
—
|
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 cooked curd | Statement: [Parmigiano Reggiano, cookingTemperature, high-temperature cooked curd]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cookingTemperature Context triple: [Parmigiano Reggiano, cookingTemperature, high-temperature cooked curd]
-
A.
requiresCookingTemperature
chosen
Indicates that performing the action or preparing the item necessitates reaching or maintaining a specific cooking temperature.
-
B.
brewingTemperature
Indicates the specific temperature at which a brewing process is carried out.
-
C.
typicalCookingTime
Indicates the usual duration required to cook something under standard or commonly accepted conditions.
-
D.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
E.
recommendedServingTemperature
Indicates the temperature at which something (typically food or drink) is advised to be served for optimal use or enjoyment.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbeef57881909245c8a5374a8111 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.