Triple
T13713099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naseeb Abdul Juma |
E328822
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Ali Kiba |
E1056848
|
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: Ali Kiba | Statement: [Naseeb Abdul Juma, associatedAct, Ali Kiba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ali Kiba Context triple: [Naseeb Abdul Juma, associatedAct, Ali Kiba]
-
A.
Ali Kiba
Ali Kiba is a Tanzanian singer and songwriter known as one of East Africa’s leading Bongo Flava artists.
-
B.
Hassan Kadam
Hassan Kadam is a gifted young Indian chef whose culinary talent and personal journey drive the narrative of the film "The Hundred-Foot Journey."
-
C.
Amir Kano
Amir Kano is the traditional Muslim ruler and highest-ranking royal authority of the historic Kano Emirate in northern Nigeria.
-
D.
Ali Saleh Kiba
chosen
Ali Saleh Kiba is a Tanzanian singer and songwriter renowned as one of East Africa’s most popular and influential Bongo Flava artists.
-
E.
Ali Gaji
Ali Gaji was a historical ruler (Mai) of the Bornu Empire in Central Africa, noted for consolidating power and strengthening the state.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd4395e8c0819098719c8cd344aa33 |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a845a29c81908096a785f5af5521 |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:54 p.m.