Triple

T13507569
Position Surface form Disambiguated ID Type / Status
Subject Get Shorty E321051 entity
Predicate starring P1507 FINISHED
Object Dennis Farina E197270 NE FINISHED

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: Dennis Farina | Statement: [Get Shorty, starring, Dennis Farina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dennis Farina
Context triple: [Get Shorty, starring, Dennis Farina]
  • A. Dennis Farina chosen
    Dennis Farina was an American actor and former Chicago police officer best known for his tough-guy roles in films like "Get Shorty" and on TV series such as "Law & Order."
  • B. Dennis Franz
    Dennis Franz is an American actor best known for his acclaimed portrayal of Detective Andy Sipowicz on the television series "NYPD Blue."
  • C. William Katt
    William Katt is an American actor best known for starring in the 1980s television series "The Greatest American Hero" and appearing in films such as "Carrie."
  • D. Burt Young
    Burt Young was an American character actor best known for his Oscar-nominated role as Paulie Pennino, Rocky Balboa’s gruff but loyal friend, in the Rocky film series.
  • E. Jason Beghe
    Jason Beghe is an American actor best known for his role as tough, gravel-voiced Sergeant Hank Voight in the television series "Chicago P.D."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf8259a08190ada13c4a3078f07d completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7548e51b881909a3384812556bc3d completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.