Triple
T20410539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whatever Gets You Through the Day |
E500575
|
entity |
| Predicate | performerMember |
P22076
|
FINISHED |
| Object | Tunde Baiyewu |
—
|
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: Tunde Baiyewu | Statement: [Whatever Gets You Through the Day, performerMember, Tunde Baiyewu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tunde Baiyewu Context triple: [Whatever Gets You Through the Day, performerMember, Tunde Baiyewu]
-
A.
Tunde Baiyewu
chosen
Tunde Baiyewu is a British-Nigerian singer best known as the lead vocalist of the soul and pop duo Lighthouse Family.
-
B.
Michael Olatunji
Michael Olatunji, better known as Babatunde Olatunji, was a pioneering Nigerian drummer and bandleader who popularized African percussion and rhythms in American jazz and world music.
-
C.
Tunde Williams
Tunde Williams is a musician best known for his role in Fela Kuti’s influential Afrobeat band Africa 70.
-
D.
Tunde King
Tunde King was a pioneering Nigerian musician credited with helping to develop and popularize early Jùjú music in the 1930s.
-
E.
Samson Kayo
Samson Kayo is a British actor and comedian known for his roles in television comedies such as "Timewasters," "Famalam," and "Bloods."
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3ecb348190ae777f6276037828 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.