Triple
T12410593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | African Giant |
E296502
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | DJDS |
E977287
|
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: DJDS | Statement: [African Giant, producer, DJDS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJDS Context triple: [African Giant, producer, DJDS]
-
A.
DJDS
chosen
DJDS is an American electronic music production duo known for blending house, R&B, and gospel influences and collaborating with major artists across hip-hop and pop.
-
B.
.dj
.dj is the country code top-level domain (ccTLD) assigned to Djibouti on the internet.
-
C.
DJU
DJU is the ticker symbol used by financial data vendors to represent the Dow Jones Utility Average, a stock market index tracking major U.S. utility companies.
-
D.
RJD2
RJD2 is an American producer and DJ known for his eclectic, sample-based instrumental hip hop and electronic music, including the track used as the opening theme for the TV series "Mad Men."
-
E.
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.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d4b86c88190afba0de15b34eee9 |
completed | April 10, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6348af5a8819083a075d145b15fd4 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.