Triple
T8007475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Jazzy |
E186397
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Rema |
E59915
|
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: Rema | Statement: [Don Jazzy, collaboratedWith, Rema]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rema Context triple: [Don Jazzy, collaboratedWith, Rema]
-
A.
Rema
chosen
Rema is a Nigerian singer, songwriter, and rapper known for his influential role in modern Afrobeats and hit songs like "Dumebi" and "Calm Down."
-
B.
Rema
Rema is the widely used acronym for Rabbi Moshe Isserles, a prominent 16th-century Polish rabbi and halakhic authority best known for his glosses on the Shulchan Aruch.
-
C.
Bessi
The Bessi were an ancient Thracian tribe known from classical sources for inhabiting mountainous regions and serving as fierce, often rebellious, warriors and priests.
-
D.
Josue
Josue is a given name, commonly used in Spanish and Portuguese, that corresponds to the biblical name Joshua.
-
E.
MØ
MØ is a Danish singer and songwriter known for her electro-pop sound and international hits like "Lean On" with Major Lazer.
- 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_69cb3cf8a6048190970685a83fd2f59d |
completed | March 31, 2026, 3:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe12c068c8190a6ea7e924a7748c6 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:18 p.m.