Triple
T22129044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alapalooza |
E546861
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Tony Papa |
—
|
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: Tony Papa | Statement: [Alapalooza, producer, Tony Papa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Papa Context triple: [Alapalooza, producer, Tony Papa]
-
A.
Tony Papa
chosen
Tony Papa is a music producer and audio engineer known for his work on albums such as "Bad Hair Day" by "Weird Al" Yankovic.
-
B.
Tony Papp
Tony Papp is the son of influential American theatrical producer and founder of The Public Theater, Joseph Papp.
-
C.
Tony Palermo
Tony Palermo is an American drummer best known for his work with the rock band Papa Roach.
-
D.
Tony Rome
Tony Rome is a 1967 neo-noir detective film starring Frank Sinatra as a hard-boiled private investigator in Miami.
-
E.
Robert Paparemborde
Robert Paparemborde was a prominent French rugby union prop who earned numerous caps for France and became one of the standout forwards of his era.
- 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.