Triple
T13713092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naseeb Abdul Juma |
E328822
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Naseeb Junior |
E327787
|
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: Naseeb Junior | Statement: [Naseeb Abdul Juma, hasChild, Naseeb Junior]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naseeb Junior Context triple: [Naseeb Abdul Juma, hasChild, Naseeb Junior]
-
A.
Naseeb Jr.
chosen
Naseeb Jr. is the son of Tanzanian music star Diamond Platnumz and a young public figure known mainly through his parents’ celebrity status.
-
B.
Joy Baba Felunath
Joy Baba Felunath is a popular Bengali detective film directed by Satyajit Ray, featuring his iconic sleuth Feluda as he investigates a mysterious theft and murder in Varanasi.
-
C.
Nobbut a Lad
Nobbut a Lad is an autobiographical book by British gardener and broadcaster Alan Titchmarsh, recounting his Yorkshire childhood and early life.
-
D.
Laʼeeb
Laʼeeb is the animated, turban-like character that served as the official mascot of the 2022 FIFA World Cup in Qatar.
-
E.
Budak
Budak is a Turkish surname borne by various individuals, including academics, politicians, and public figures.
- 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_69f79d56a90081908158dcf4ee061fb6 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:54 p.m.