Triple
T8008773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glitter |
E186429
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | DJ Camper |
E180776
|
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 Camper | Statement: [Glitter, producer, DJ Camper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJ Camper Context triple: [Glitter, producer, DJ Camper]
-
A.
DJ Camper
chosen
DJ Camper is a Grammy-nominated American record producer and songwriter known for his work with major R&B and hip-hop artists.
-
B.
DJ Dahi
DJ Dahi is an American record producer and DJ known for his innovative, genre-blending work with major hip-hop and R&B artists.
-
C.
DJ Tambe
DJ Tambe is an award-winning tattoo artist best known for his multiple championship wins on the reality competition series "Ink Master" and his role as a judge on the show.
-
D.
DJ Toomp
DJ Toomp is an American record producer and DJ best known for his influential work in Southern hip hop, including crafting hits for artists like T.I. and Kanye West.
-
E.
DJ Shok
DJ Shok is a hip-hop producer best known for his work with DMX, including producing the acclaimed track "Slippin'."
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d6f76408190a1312369521a187a |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc569e90d48190a1bf1495496017f8 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:19 p.m.