Triple
T21769125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walk Hard: The Dewey Cox Story |
E537375
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Matt Besser |
—
|
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: Matt Besser | Statement: [Walk Hard: The Dewey Cox Story, starring, Matt Besser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Besser Context triple: [Walk Hard: The Dewey Cox Story, starring, Matt Besser]
-
A.
Matt Besser
chosen
Matt Besser is an American comedian, actor, and improviser best known as a founding member of the influential Upright Citizens Brigade comedy troupe.
-
B.
Eugene Mirman
Eugene Mirman is a Russian-born American comedian and actor best known for his stand-up comedy and voice work on animated television series.
-
C.
Jon Barinholtz
Jon Barinholtz is an American actor and comedian known for his roles on television series such as "Superstore" and "American Auto."
-
D.
Paul F. Tompkins
Paul F. Tompkins is an American comedian, actor, and writer known for his stand-up, podcast appearances, and character roles in television and film.
-
E.
Hannibal Buress
Hannibal Buress is an American stand-up comedian, actor, writer, and producer known for his laid-back delivery, sharp observational humor, and roles in shows like "Broad City" and films such as "Spider-Man: Homecoming."
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031ac10808190837a0f69c4f8a02d |
completed | April 28, 2026, 4:03 a.m. |
Created at: April 16, 2026, 6:51 p.m.