Triple
T4411754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American cuisine |
E94866
|
entity |
| Predicate | includesMealType |
P19941
|
FINISHED |
| Object | breakfast foods |
—
|
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: breakfast foods | Statement: [American cuisine, includesMealType, breakfast foods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesMealType Context triple: [American cuisine, includesMealType, breakfast foods]
-
A.
hasMealType
chosen
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
-
B.
hasSpecialMeal
Indicates that an entity provides, is assigned, or is associated with a designated special meal option.
-
C.
cateringIncludes
Indicates that a catering service or arrangement encompasses or provides the specified item, service, or component as part of its offering.
-
D.
includesFeedingType
Indicates that one entity encompasses or specifies a particular type or category of feeding associated with another entity.
-
E.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e656dc819093ca8395d7334006 |
completed | March 13, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:29 p.m.