Triple

T18372939
Position Surface form Disambiguated ID Type / Status
Subject WKRP in Cincinnati E446231 entity
Predicate hasMainCharacter P1183 FINISHED
Object Les Nessman 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: Les Nessman | Statement: [WKRP in Cincinnati, hasMainCharacter, Les Nessman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Les Nessman
Context triple: [WKRP in Cincinnati, hasMainCharacter, Les Nessman]
  • A. Les Nessman chosen
    Les Nessman is a bumbling, earnest news reporter character best known from the WKRP in Cincinnati television sitcom franchise.
  • B. Max Nanasy
    Max Nanasy is a software engineer and writer known for contributions to programming tools and documentation, including work related to JSON5.
  • C. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • D. Leslie
    Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
  • E. Leslie
    Leslie is the given name of American actress and singer Leslie Uggams, known for her work on stage, television, and film.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e517561edc8190b5d2834707ab662b completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:45 a.m.