Triple
T13793701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drogas Wave |
E331460
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | DJ Dahi |
E135452
|
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 Dahi | Statement: [Drogas Wave, producer, DJ Dahi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJ Dahi Context triple: [Drogas Wave, producer, DJ Dahi]
-
A.
DJ Dahi
chosen
DJ Dahi is an American record producer and DJ known for his innovative, genre-blending work with major hip-hop and R&B artists.
-
B.
DJ Shok
DJ Shok is a hip-hop producer best known for his work with DMX, including producing the acclaimed track "Slippin'."
-
C.
DJ Lord
DJ Lord is an American turntablist and hip hop DJ best known as the longtime touring and performance DJ for the influential rap group Public Enemy.
-
D.
DJ Die
DJ Die is a British drum and bass DJ and producer from Bristol, known for his influential role in shaping the city’s distinctive sound and its global reputation in electronic music.
-
E.
Dâm-Funk
Dâm-Funk is an American modern-funk musician and producer known for reviving and updating the classic West Coast boogie and G-funk sound.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0259b0e4819081c11ced694384fb |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce667c248190a9d0a0f1e9e228ae |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:11 p.m.