Triple
T22418461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obafemi Awolowo |
E554183
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Obafemi |
—
|
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: Obafemi | Statement: [Obafemi Awolowo, givenName, Obafemi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Obafemi Context triple: [Obafemi Awolowo, givenName, Obafemi]
-
A.
Obafemi
chosen
Obafemi is a Nigerian given name most notably borne by former professional footballer Obafemi Martins.
-
B.
Bim Afolami
Bim Afolami is a British Conservative politician and lawyer who has served as a Member of Parliament since 2017 and has held various roles in economic and financial policy.
-
C.
Remi Adedeji
Remi Adedeji is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Adedeji.
-
D.
Kevin Olusola
Kevin Olusola is an American musician best known as the beatboxer and cellist of the a cappella group Pentatonix.
-
E.
Jimmy Odukoya
Jimmy Odukoya is a Nigerian actor and pastor best known internationally for his role in the historical epic film "The Woman King."
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15948dcdc81909d0a792c4498fa70 |
completed | April 29, 2026, 1:05 a.m. |
Created at: April 16, 2026, 8:46 p.m.