Triple
T18685284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoga Hosers |
E456843
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Tony Hale |
—
|
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: Tony Hale | Statement: [Yoga Hosers, starring, Tony Hale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Hale Context triple: [Yoga Hosers, starring, Tony Hale]
-
A.
Tony Hale
chosen
Tony Hale is an American actor and comedian best known for his Emmy-winning roles in the television series "Arrested Development" and "Veep."
-
B.
Hugh Dennis
Hugh Dennis is a British comedian, actor, and writer best known for his work on the sketch show "The Mary Whitehouse Experience" and the sitcom "Outnumbered."
-
C.
Julian Barratt
Julian Barratt is an English comedian, actor, musician, and writer best known as one half of the surreal comedy duo behind The Mighty Boosh.
-
D.
Michael Ian Black
Michael Ian Black is an American comedian, actor, writer, and director known for his work on "The State," "Stella," and numerous stand-up and television appearances.
-
E.
Kyle Dunnigan
Kyle Dunnigan is an American comedian, actor, and writer known for his sketch work, stand-up, and frequent collaborations with Amy Schumer.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2c58188190b906c9ab080a76ff |
completed | April 19, 2026, 10:46 p.m. |
Created at: April 10, 2026, 11:49 a.m.