Triple
T8023246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Offset |
E186789
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Kiari Kendrell Cephus |
E707763
|
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: Kiari Kendrell Cephus | Statement: [Offset, birthName, Kiari Kendrell Cephus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiari Kendrell Cephus Context triple: [Offset, birthName, Kiari Kendrell Cephus]
-
A.
Kiari Cephus
chosen
Kiari Cephus, better known by his stage name Offset, is an American rapper and member of the hip hop trio Migos.
-
B.
Terria Joseph
Terria Joseph is an American actress and theater professional best known as the mother of singer-songwriter Alicia Keys.
-
C.
Kendal Richardson
Kendal Richardson is a political figure who ran for mayor in the 2023 Dallas mayoral election.
-
D.
Andell Wilkerson
Andell Wilkerson is a witty, down-to-earth supporting character from the sitcom "Moesha," known for being Moesha's close friend and a source of comic relief and guidance.
-
E.
Devereaux Jennings
Devereaux Jennings was a pioneering cinematographer best known as the founder of the American Society of Cinematographers, a key professional organization in the film industry.
- 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_69ca82ad4e2c8190a693e3c9e30fe66f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8fb6788190a16413051ec26988 |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbe4211bc8190a784c19f11f17a39 |
completed | April 1, 2026, 6:42 a.m. |
Created at: March 30, 2026, 5:21 p.m.