Triple
T4206783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coq au vin |
E93800
|
entity |
| Predicate | typicalPreparationTime |
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: [Coq au vin, typicalPreparationTime, several hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPreparationTime Context triple: [Coq au vin, typicalPreparationTime, several hours]
-
A.
typicalCookingTime
chosen
Indicates the usual duration required to cook something under standard or commonly accepted conditions.
-
B.
typicalPreparation
Indicates the usual or standard way in which something is prepared or made.
-
C.
traditionalPreparation
Indicates that something is prepared or made using customary, long-established methods or techniques associated with a particular culture or practice.
-
D.
preparationPeriod
Indicates the time span allocated before an event or action during which necessary preparations are made.
-
E.
brewingTime
Indicates the duration required to brew or prepare a beverage or similar concoction.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:03 p.m.