Triple
T7963865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D'banj |
E184946
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Koko Master |
E184928
|
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: Koko Master | Statement: [D'banj, associatedWith, Koko Master]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koko Master Context triple: [D'banj, associatedWith, Koko Master]
-
A.
Koko
Koko is a prominent Itsekiri town in Nigeria’s Niger Delta, known historically as a key riverine trading and port community.
-
B.
Koko
chosen
Koko is a popular Afrobeat/afropop song by Nigerian musician D'banj that helped cement his status as a leading figure in contemporary African music.
-
C.
Koko
Koko was a canine actor best known for playing the title role in the Australian film "Red Dog."
-
D.
Koko Nor
Koko Nor, also known as Qinghai Lake, is the largest saltwater lake in China, located on the northeastern edge of the Tibetan Plateau.
-
E.
Kiko
Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
- 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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b9f577481908589d10fdc486abb |
completed | March 31, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc566604e881908792c7155a370e4c |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:12 p.m.