Triple
T16849129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Kwesi Mensah |
E409623
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | U Mad |
E409628
|
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: U Mad | Statement: [Victor Kwesi Mensah, notableWork, U Mad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: U Mad Context triple: [Victor Kwesi Mensah, notableWork, U Mad]
-
A.
U Mad
chosen
"U Mad" is a hip-hop single by American rapper Vic Mensa featuring Kanye West, known for its aggressive energy and confrontational lyrics.
-
B.
Mada
Mada is an ethnic group in central Nigeria, known for its distinct language and culture and for living in close proximity to the Eggon people.
-
C.
M.A.D.
M.A.D. is the nefarious criminal organization led by the villain Dr. Claw in the animated series "Inspector Gadget."
-
D.
Mado
Mado is a French film written by Gérard Brach, known as one of his notable screenwriting works.
-
E.
Madadeni
Madadeni is a township in KwaZulu-Natal, South Africa, situated near Newcastle and known as a large residential and industrial area in the 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b377b5d881909f0878dd9957f3bc |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb1f02648190937c692af83843dc |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.