Triple
T21874326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KIKA |
E540090
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object | Tory Lanez |
—
|
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: Tory Lanez | Statement: [KIKA, featuredArtist, Tory Lanez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tory Lanez Context triple: [KIKA, featuredArtist, Tory Lanez]
-
A.
Tory Lanez
chosen
Tory Lanez is a Canadian rapper, singer, and songwriter known for his melodic blend of hip hop and R&B and for hit projects like "Chixtape" and "Daystar."
-
B.
Tee Grizzley
Tee Grizzley is an American rapper from Detroit known for his gritty storytelling and breakout hit "First Day Out."
-
C.
Ice Trae
Ice Trae is the popular nickname of NBA All-Star point guard Trae Young, highlighting his clutch shooting and cool demeanor under pressure.
-
D.
Nasty C
Nasty C is a South African rapper, songwriter, and record producer known for his versatile flow and prominent role in the African hip-hop scene.
-
E.
Trippie Redd
Trippie Redd is an American rapper and singer known for his melodic, emo-influenced trap style and hits like "Love Scars" and "Topanga."
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f338757c81908005bfedb52b03cc |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 7:01 p.m.