Triple
T9854029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breakfast of Champions |
E239539
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Omar Epps |
E598558
|
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: Omar Epps | Statement: [Breakfast of Champions, hasCastMember, Omar Epps]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omar Epps Context triple: [Breakfast of Champions, hasCastMember, Omar Epps]
-
A.
Omar Epps
chosen
Omar Epps is an American actor and producer best known for his roles in films like "Love & Basketball" and the TV series "House."
-
B.
Michael Elliot Epps
Michael Elliot Epps is an American stand-up comedian and actor best known for his roles in films like the "Friday" series and numerous comedy specials.
-
C.
Miles Brown
Miles Brown is an American actor and dancer best known for playing Jack Johnson on the ABC sitcom "Black-ish."
-
D.
Derek Luke
Derek Luke is an American actor known for his breakout role in "Antwone Fisher" and performances in films like "Glory Road" and "Captain America: The First Avenger."
-
E.
Michael Ealy
Michael Ealy is an American actor known for his roles in films like "Barbershop," "Think Like a Man," and "2 Fast 2 Furious," as well as various television series.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb376d32c819089381cf6ed83629d |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20d511e348190aab23a45048ea7b3 |
completed | April 5, 2026, 7:20 a.m. |
Created at: March 30, 2026, 8:34 p.m.