Triple

T5589237
Position Surface form Disambiguated ID Type / Status
Subject NYPD Blue E146833 entity
Predicate starredActor P5563 FINISHED
Object Dennis Franz E93505 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 Franz | Statement: [NYPD Blue, starredActor, Dennis Franz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dennis Franz
Context triple: [NYPD Blue, starredActor, Dennis Franz]
  • A. Dennis Franz chosen
    Dennis Franz is an American actor best known for his acclaimed portrayal of Detective Andy Sipowicz on the television series "NYPD Blue."
  • B. 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."
  • C. Dennis Farina
    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."
  • D. Andre Braugher
    Andre Braugher is an American actor acclaimed for his powerful dramatic roles and his Emmy-winning performances in both television and film.
  • E. Linus Roache
    Linus Roache is an English actor known for his roles in film and television, including prominent performances in series such as "Homeland" and "Law & Order."
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0209ff5d88190843b6d134390ab71 completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d342f7881908a79522692e8f7f9 completed March 22, 2026, 8:12 p.m.
Created at: March 22, 2026, 3:38 p.m.