Triple
T22873690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabu Kabu |
E567264
|
entity |
| Predicate | hasCoverArtBy |
P5936
|
FINISHED |
| Object | Joey Hi-Fi |
—
|
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: Joey Hi-Fi | Statement: [Kabu Kabu, hasCoverArtBy, Joey Hi-Fi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joey Hi-Fi Context triple: [Kabu Kabu, hasCoverArtBy, Joey Hi-Fi]
-
A.
Joey Hi-Fi
chosen
Joey Hi-Fi is a South African illustrator and graphic designer renowned for his intricate, high-concept book cover art, particularly in the science fiction and fantasy genres.
-
B.
Mojo Jojo
Mojo Jojo is the main simian supervillain in *The Powerpuff Girls*, known for his genius-level intellect, elaborate evil schemes, and distinctive exposed-brain helmet.
-
C.
Mr. Music
Mr. Music is a 1950 American musical comedy film starring Bing Crosby, adapted from Samson Raphaelson’s play "Accent on Youth."
-
D.
Darrell the DJ
Darrell the DJ is a disc jockey persona known for mixing and playing music, typically in live or event settings.
-
E.
Jo-Jo
Jo-Jo is a young child character from the film "Baby Boy," appearing as the son of Yvette.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f56d6448190ada4aef08eac2bed |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.