Triple
T33936351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akita Komachi rice |
E870042
|
entity |
| Predicate | suitableForDish |
P25824
|
FINISHED |
| Object | sushi |
—
|
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: sushi | Statement: [Akita Komachi rice, suitableForDish, sushi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suitableForDish Context triple: [Akita Komachi rice, suitableForDish, sushi]
-
A.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
B.
isTypicallyEatenWith
Indicates that one item is commonly consumed together with another as part of the same eating occasion or dish.
-
C.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
D.
intendedFood
Indicates that one entity is the food item that another entity plans or is meant to eat or consume.
-
E.
culinaryUse
chosen
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_69f3499a59788190bff762a891471b31 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:49 a.m.