Triple

T13564441
Position Surface form Disambiguated ID Type / Status
Subject Dann Florek E323995 entity
Predicate hasActedIn P15620 FINISHED
Object Matlock E424732 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: Matlock | Statement: [Dann Florek, hasActedIn, Matlock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matlock
Context triple: [Dann Florek, hasActedIn, Matlock]
  • A. Matlock
    Matlock is a historic spa and market town in Derbyshire, England, known for its picturesque setting in the Derwent Valley and its role as the county’s administrative centre.
  • B. Matlock chosen
    Matlock is an American legal drama television series starring Andy Griffith as a shrewd, folksy defense attorney known for his courtroom showdowns and investigative skills.
  • C. Kojak
    Kojak is a 1970s American television crime drama series centered on the tough, lollipop-licking New York City detective Theo Kojak, played by Telly Savalas.
  • D. Mannix
    Mannix is an American television detective series from the late 1960s and 1970s, centered on the tough, resourceful private investigator Joe Mannix.
  • E. Jim Rockford
    Jim Rockford is the wisecracking, down-on-his-luck private investigator protagonist of the 1970s television series "The Rockford Files," portrayed by James Garner.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00bbe848190bb33efe2af528295 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75daf1bfc8190bf22eb9ef242f54f completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:47 p.m.