Triple
T3200555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chef Mickey's |
E67038
|
entity |
| Predicate | hasDiningType |
P35620
|
FINISHED |
| Object | character dining |
—
|
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: character dining | Statement: [Chef Mickey's, hasDiningType, character dining]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningType Context triple: [Chef Mickey's, hasDiningType, character dining]
-
A.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
B.
hasCharacterDining
chosen
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
C.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
E.
hasMealType
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9aedef08190824bdf508f85f06f |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e05e4f48190adbe4366cdba2349 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.