Triple
T20645287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spree |
E507339
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Kyle Mooney |
—
|
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: Kyle Mooney | Statement: [Spree, starring, Kyle Mooney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyle Mooney Context triple: [Spree, starring, Kyle Mooney]
-
A.
Kyle Mooney
chosen
Kyle Mooney is an American comedian, actor, and writer best known as a former Saturday Night Live cast member and for his offbeat, awkwardly humorous characters and sketches.
-
B.
Jon Barinholtz
Jon Barinholtz is an American actor and comedian known for his roles on television series such as "Superstore" and "American Auto."
-
C.
Matt Besser
Matt Besser is an American comedian, actor, and improviser best known as a founding member of the influential Upright Citizens Brigade comedy troupe.
-
D.
Nick Kroll
Nick Kroll is an American comedian, actor, writer, and producer known for his sketch series "Kroll Show," his work on "The League," and co-creating and voicing characters in the animated series "Big Mouth."
-
E.
Paul Scheer
Paul Scheer is an American actor, comedian, writer, and podcaster known for his work in improvisational comedy, television series like "The League," and the movie-focused podcast "How Did This Get Made?"
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1dd79481909de985d03ab861c2 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.