Triple
T14350153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pretty Toney Album |
E355831
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | DJ Kayslay |
E594347
|
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: DJ Kayslay | Statement: [The Pretty Toney Album, producer, DJ Kayslay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJ Kayslay Context triple: [The Pretty Toney Album, producer, DJ Kayslay]
-
A.
DJ Kayslay
chosen
DJ Kay Slay was an influential New York hip-hop DJ and mixtape pioneer known for his street-centric tapes, radio shows, and collaborations with major rap artists.
-
B.
DJ Kaywise
DJ Kaywise is a popular Nigerian disc jockey and music producer known for his hit street anthems, mixtapes, and collaborations with top Afrobeats artists.
-
C.
DJ Klem
DJ Klem is a Nigerian music producer and DJ known for crafting polished, genre-blending beats for prominent Afrobeats and hip-hop artists.
-
D.
K1lla Beatz
K1lla Beatz is a music producer known for crafting hip-hop and rap instrumentals, including work on the project "4:21... The Day After."
-
E.
DJ Mekalek
DJ Mekalek is a hip-hop DJ and producer known for his intricate turntablism, underground collaborations, and work with groups like Time Machine.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f4e1e588190bdc7aaf7a2819948 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c4335e481909d4db39b8d25edc9 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:14 a.m.