Triple
T12431264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayodeji Ibrahim Balogun |
E297033
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Joro |
E292163
|
NE FINISHED |
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: Joro | Statement: [Ayodeji Ibrahim Balogun, notableWork, Joro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joro Context triple: [Ayodeji Ibrahim Balogun, notableWork, Joro]
-
A.
Joro
chosen
"Joro" is a popular Afrobeats song by Nigerian artist Wizkid, known for its smooth melodies and romantic themes.
-
B.
Jauor
Jauor is an alternative name for the Yawuru, an Aboriginal Australian people traditionally associated with the Broome region of Western Australia.
-
C.
Vráble
Vráble is a small town in western Slovakia known for its agricultural surroundings and location near the city of Nitra.
-
D.
Yorgi
Yorgi is the main Russian crime lord and antagonist in the action film "xXx," portrayed by actor Marton Csokas.
-
E.
Djugu
Djugu is a town and administrative center in northeastern Democratic Republic of the Congo, located within the conflict-affected Ituri region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7f2fd08190ab959742dbd8f9c0 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6349d29c481909a37fd386cc06575 |
completed | May 2, 2026, 5:30 p.m. |
Created at: April 8, 2026, 9:55 p.m.