Triple

T16325399
Position Surface form Disambiguated ID Type / Status
Subject Kari Lizer E396398 entity
Predicate castMemberOf P7010 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: [Kari Lizer, castMemberOf, Matlock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matlock
Context triple: [Kari Lizer, castMemberOf, 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. Van der Valk
    Van der Valk is a British television crime drama series centered on a Dutch detective solving cases in Amsterdam.
  • E. Mannix
    Mannix is an American television detective series from the late 1960s and 1970s, centered on the tough, resourceful private investigator Joe Mannix.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e296b9dcb88190beb0ca2206729175 completed April 17, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002da915ac8190820acbe0db72c8a1 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:06 a.m.