Triple
T7116810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karelian stew |
E165839
|
entity |
| Predicate | usesCookingVessel |
P61222
|
FINISHED |
| Object | casserole dish |
—
|
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: casserole dish | Statement: [Karelian stew, usesCookingVessel, casserole dish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCookingVessel Context triple: [Karelian stew, usesCookingVessel, casserole dish]
-
A.
servingVessel
Indicates that one entity functions as the container or vessel used to serve another entity (such as food or drink).
-
B.
possibleFermentationVessel
Indicates that something can serve as a suitable container or environment in which fermentation may take place.
-
C.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
D.
isUsuallyCookedIn
chosen
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
E.
dishType
Indicates the classification of a dish according to its culinary category or role (e.g., appetizer, main course, dessert).
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e617a528819085d4b8e1b5699966 |
completed | March 27, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.