Triple
T20611280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogan |
E506453
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Joe Rogan |
—
|
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: Joe Rogan | Statement: [Rogan, hasNotableBearer, Joe Rogan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Rogan Context triple: [Rogan, hasNotableBearer, Joe Rogan]
-
A.
Joe Rogan
chosen
Joe Rogan is an American stand-up comedian, podcast host, and UFC commentator best known for "The Joe Rogan Experience," one of the world’s most popular long-form interview podcasts.
-
B.
Bullet Joe Rogan
Bullet Joe Rogan was an American Negro league baseball star of the early 20th century, renowned as a dominant two-way player (both pitcher and outfielder) and a key figure for the Kansas City Monarchs.
-
C.
Tom Rogan
Tom Rogan is an abusive and controlling husband from Stephen King’s horror novel "It," known for his relationship with Beverly Marsh.
-
D.
Theo Von
Theo Von is an American stand-up comedian and podcast host known for his Southern storytelling style and offbeat, self-deprecating humor.
-
E.
Marc Maron
Marc Maron is an American stand-up comedian, actor, and podcaster best known for his influential podcast "WTF with Marc Maron" and his roles in television and film.
- 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aad81bdc8190aa6f6164f406a468 |
completed | April 20, 2026, 10:38 p.m. |
Created at: April 16, 2026, 11:41 a.m.