Triple
T31755436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horst |
E810544
|
entity |
| Predicate | roleInKitchen |
P147089
|
FINISHED |
| Object | line cook |
—
|
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: line cook | Statement: [Horst, roleInKitchen, line cook]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInKitchen Context triple: [Horst, roleInKitchen, line cook]
-
A.
roleInFood
Indicates the functional role or purpose that an entity has within a food item, product, or context (e.g., ingredient, flavoring, preservative).
-
B.
worksInKitchenAt
chosen
Indicates that an entity performs work or duties in the kitchen area of a specified location or organization.
-
C.
roleInCheeseRind
Indicates the specific functional or structural role an entity plays in the formation, maintenance, or characteristics of a cheese rind.
-
D.
roleInCoco
Indicates that an entity serves a specific role or function within the context of the COCO dataset or framework.
-
E.
roleInCheese
Indicates that an entity participates in the production, composition, or classification of a cheese with a specific functional role.
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
Created at: April 30, 2026, 11:29 p.m.