Triple
T7963749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fally Ipupa |
E184943
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | R. Kelly |
E69748
|
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: R. Kelly | Statement: [Fally Ipupa, associatedAct, R. Kelly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R. Kelly Context triple: [Fally Ipupa, associatedAct, R. Kelly]
-
A.
R. Kelly
chosen
R. Kelly is an American R&B singer, songwriter, and record producer known for his influential 1990s and 2000s hits as well as his later criminal convictions for sexual abuse.
-
B.
Chris Brown
Chris Brown is an American singer, songwriter, dancer, and actor known for his R&B and pop hits as well as his dynamic performances.
-
C.
Chris Brown
Chris Brown is a film producer known for his work on the World War II drama "The Railway Man."
-
D.
Christopher Brown
Christopher Brown is an architect known for his work on the National Theatre in London.
-
E.
Red Kelly
Red Kelly was a Canadian Hall of Fame ice hockey defenseman and later politician, renowned for his stellar NHL career with the Detroit Red Wings and Toronto Maple Leafs.
- 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_69cbe093f00881909317eb4dd4fa1393 |
completed | March 31, 2026, 2:56 p.m. |
Created at: March 30, 2026, 5:12 p.m.