Triple

T9340772
Position Surface form Disambiguated ID Type / Status
Subject The Comedian E224757 entity
Predicate teamAffiliation P3753 FINISHED
Object Crimebusters E792671 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: Crimebusters | Statement: [The Comedian, teamAffiliation, Crimebusters]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Crimebusters
Context triple: [The Comedian, teamAffiliation, Crimebusters]
  • A. Crimebusters chosen
    Crimebusters is a superhero team in the Watchmen universe formed by a new generation of costumed vigilantes attempting to address rising crime and social unrest.
  • B. Crime Busters
    Crime Busters is a 1977 Italian action-comedy film starring Terence Hill and Bud Spencer as bumbling yet effective crime-fighting partners in Miami.
  • C. Cops
    Cops is a long-running American reality television series that follows police officers on duty as they respond to real-life incidents and arrests.
  • D. Beverly Hills Cop
    Beverly Hills Cop is a 1984 action-comedy film starring Eddie Murphy as a wisecracking Detroit detective who investigates a murder in the upscale city of Beverly Hills.
  • E. Bad Cop
    Bad Cop is a central antagonist-turned-ally in *The Lego Movie*, depicted as a conflicted Lego police officer with a split good cop/bad cop personality.
  • 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_69ca84286fcc81909f6e7fd7a7e862a2 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4bae2e2481909effc2dc89a642c5 completed April 1, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3bad4388190ac53657027262a46 completed April 4, 2026, 11:19 a.m.
Created at: March 30, 2026, 7:40 p.m.