Triple
T22948300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil in a Blue Dress |
E569934
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Tom Sizemore |
—
|
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: Tom Sizemore | Statement: [Devil in a Blue Dress, starredActor, Tom Sizemore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Sizemore Context triple: [Devil in a Blue Dress, starredActor, Tom Sizemore]
-
A.
Tom Sizemore
chosen
Tom Sizemore was an American character actor known for his intense supporting roles in gritty war and crime films such as "Saving Private Ryan," "Heat," and "Black Hawk Down."
-
B.
Nicolas Cage
Nicolas Cage is an American actor known for his intense and eclectic performances across action, drama, and independent films.
-
C.
Darren Roy Ashmore
Darren Roy Ashmore is a film and television producer known for his work on the documentary "Kevin Pollak's Misery Loves Comedy."
-
D.
Ed Norton
Ed Norton is the jovial, dim-witted sewer worker and best friend of Ralph Kramden in the classic American television sitcom "The Honeymooners."
-
E.
Matthew Lillard
Matthew Lillard is an American actor and director best known for his energetic, often comedic performances in films such as "Scream," "Scooby-Doo," and "Hackers."
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819fbf8c8190ad80c93f1507aa73 |
completed | April 29, 2026, 3:57 a.m. |
Created at: April 17, 2026, 3:46 p.m.