Triple
T22335209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cedric Yarbrough |
E552127
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Cedric Yarbrough |
—
|
NE NERFINISHED |
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: Cedric Yarbrough | Statement: [Cedric Yarbrough, name, Cedric Yarbrough]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cedric Yarbrough Context triple: [Cedric Yarbrough, name, Cedric Yarbrough]
-
A.
Cedric Yarbrough
chosen
Cedric Yarbrough is an American actor and comedian best known for his roles on the TV series "Reno 911!" and for voicing characters in animated shows such as "The Boondocks."
-
B.
Derrick Trotman
Derrick Trotman is a music producer known for his work on the track "Umi Says."
-
C.
Clifton Powell
Clifton Powell is an American character actor known for his prolific work in film and television, often portraying intense, streetwise, or authoritative supporting roles.
-
D.
Dedrick Johnson
Dedrick Johnson is an American local politician who serves as the mayor of Texas City, Texas.
-
E.
Melvin Odoom
Melvin Odoom is a British television and radio presenter and comedian known for his work on UK entertainment and music shows.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577e35f48190b11789d80182653e |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:43 p.m.