Triple
T15328728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Layers |
E366478
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Jake One |
E361730
|
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: Jake One | Statement: [Layers, producer, Jake One]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake One Context triple: [Layers, producer, Jake One]
-
A.
Jake One
chosen
Jake One is an American hip-hop record producer known for his soulful, sample-based beats and work with artists across the underground and mainstream rap scenes.
-
B.
A-Trak
A-Trak is a Canadian DJ, turntablist, and record producer known for his championship-level scratching skills and influential work in electronic and hip-hop music.
-
C.
Hudson Mohawke
Hudson Mohawke is a Scottish electronic music producer and DJ known for his influential, genre-blending work in experimental hip hop and electronic music, including production for major rap and pop artists.
-
D.
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.
-
E.
DJ Koze
DJ Koze is a German DJ and producer known for his eclectic, genre-blending electronic music and critically acclaimed albums and remixes.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dffd6f88190a0f031ee90c6a7d2 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8af92a88190bd47f1a484f25eb1 |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.