Triple
T23305346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Zizzo |
E590420
|
entity |
| Predicate | hasCollaboratedWith |
P8554
|
FINISHED |
| Object | Jason Mraz |
—
|
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: Jason Mraz | Statement: [Peter Zizzo, hasCollaboratedWith, Jason Mraz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Mraz Context triple: [Peter Zizzo, hasCollaboratedWith, Jason Mraz]
-
A.
Jason Mraz
chosen
Jason Mraz is an American singer-songwriter known for his laid-back acoustic pop style and hit songs like "I'm Yours" and "I Won't Give Up."
-
B.
John Mayer
John Mayer is an American singer-songwriter and virtuoso guitarist known for blending blues, rock, and pop in both chart-topping hits and acclaimed live performances.
-
C.
John D. Mayer
John D. Mayer is an American psychologist best known for co-developing the theory of emotional intelligence and contributing extensively to personality and emotion research.
-
D.
Daniel Powter
Daniel Powter is a Canadian singer-songwriter best known for his mid-2000s pop hit "Bad Day."
-
E.
Josh Groban
Josh Groban is an American singer, songwriter, and actor known for his powerful baritone voice and crossover classical-pop ballads.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19725b248819089e61efb82e3440f |
completed | April 29, 2026, 5:29 a.m. |
Created at: April 17, 2026, 5:05 p.m.