Triple
T4830215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swanson |
E107925
|
entity |
| Predicate | hasCuisineAssociation |
P5786
|
FINISHED |
| Object | American cuisine |
—
|
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: American cuisine | Statement: [Swanson, hasCuisineAssociation, American cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCuisineAssociation Context triple: [Swanson, hasCuisineAssociation, American cuisine]
-
A.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
B.
sharesCuisineWith
Indicates that two entities offer or are associated with the same type or style of cuisine.
-
C.
cuisineType
chosen
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
D.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
E.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.