Triple
T20269433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebo M |
E499054
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lebo M |
—
|
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: Lebo M | Statement: [Lebo M, name, Lebo M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lebo M Context triple: [Lebo M, name, Lebo M]
-
A.
Lebo M
chosen
Lebo M is a South African composer and producer best known for his African choral arrangements and vocal performances in Disney’s The Lion King franchise.
-
B.
Leabo
Leabo is a surname associated with individuals such as the American actress and novelist Brenda Joyce.
-
C.
Mandoza
Mandoza was a popular South African kwaito musician best known for his hit song "Nkalakatha" and his influential role in the country's urban music scene.
-
D.
DJ Maphorisa
DJ Maphorisa is a prominent South African DJ and record producer known for his influential role in popularizing amapiano and for producing major international and local hits.
-
E.
Sho Madjozi
Sho Madjozi is a South African rapper, singer, and songwriter known for blending Tsonga culture with contemporary hip-hop and gqom music.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675dc8e708190b840d687f134c9e8 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 11, 2026, 11:42 p.m.