Triple
T22129055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alapalooza |
E546861
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Waffle King |
—
|
NE NERFINISHED |
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: Waffle King | Statement: [Alapalooza, hasPart, Waffle King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waffle King Context triple: [Alapalooza, hasPart, Waffle King]
-
A.
Waffle King
chosen
"Waffle King" is a comedic song by "Weird Al" Yankovic that parodies fast-food culture and consumerism.
-
B.
Wahlburgers
Wahlburgers is an American casual-dining burger restaurant and bar chain co-owned by the Wahlberg family and featured in a reality TV series of the same name.
-
C.
Krispy Kreme
Krispy Kreme is an American doughnut company and coffeehouse chain best known for its Original Glazed doughnuts and signature “Hot Now” sign.
-
D.
Dairy Queen
Dairy Queen is an American fast-food and soft-serve ice cream restaurant chain known for treats like Blizzards and sundaes, as well as burgers and other quick-service fare.
-
E.
White Castle
White Castle is a medieval stone fortress in Monmouthshire, Wales, notable for its well-preserved defensive earthworks and role in the border defenses of the Welsh Marches.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12983acfc81908013f66acb31f198 |
completed | April 28, 2026, 9:41 p.m. |
Created at: April 16, 2026, 8:32 p.m.