Triple
T25040185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kokotxas de merluza |
E627084
|
entity |
| Predicate | isOftenCookedIn |
P61222
|
FINISHED |
| Object | green sauce |
—
|
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: green sauce | Statement: [kokotxas de merluza, isOftenCookedIn, green sauce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenCookedIn Context triple: [kokotxas de merluza, isOftenCookedIn, green sauce]
-
A.
isUsuallyCookedIn
chosen
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
B.
isOftenEaten
Indicates that the subject is frequently consumed as food by some agent or group.
-
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.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for another entity.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 6:08 a.m.