Triple
T3882830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | boeuf bourguignon |
E92863
|
entity |
| Predicate | requiresCookingTime |
P50957
|
FINISHED |
| Object | several hours |
—
|
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: several hours | Statement: [boeuf bourguignon, requiresCookingTime, several hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresCookingTime Context triple: [boeuf bourguignon, requiresCookingTime, several hours]
-
A.
requiresCookingTemperature
Indicates that performing the action or preparing the item necessitates reaching or maintaining a specific cooking temperature.
-
B.
typicalCookingTime
chosen
Indicates the usual duration required to cook something under standard or commonly accepted conditions.
-
C.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
D.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
E.
hasCookingQuality
Indicates that something possesses a particular characteristic or attribute related to cooking, such as flavor, texture, or suitability for a cooking method.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.