Triple
T11920165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheddar cheese |
E283630
|
entity |
| Predicate | culinaryRole |
P25824
|
FINISHED |
| Object | table cheese |
—
|
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: table cheese | Statement: [Cheddar cheese, culinaryRole, table cheese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culinaryRole Context triple: [Cheddar cheese, culinaryRole, table cheese]
-
A.
chef
Indicates that one entity serves as the cook or culinary professional responsible for preparing food for another entity or context.
-
B.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
C.
knownForDish
Indicates that an entity is recognized or notable for preparing, serving, or being associated with a particular dish.
-
D.
culinaryUse
chosen
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for another entity.
-
E.
roleInCoco
Indicates that an entity serves a specific role or function within the context of the COCO dataset or framework.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8dff77481908cacf6ad03df34ac |
completed | April 10, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3632ac8190b13e53c2b5db7125 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.