Triple
T13027654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strength of a Woman |
E326348
|
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: [Strength of a Woman, producer, DJ Camper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJ Camper Context triple: [Strength of a Woman, 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 Klem
DJ Klem is a Nigerian music producer and DJ known for crafting polished, genre-blending beats for prominent Afrobeats and hip-hop artists.
-
C.
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.
-
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.
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.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efc07488190a15f3e41ea2db45c |
completed | April 10, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c12191b08190abf4123995116ebc |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:53 p.m.