Triple

T3536691
Position Surface form Disambiguated ID Type / Status
Subject Bad Cop E74788 entity
Predicate hasAlterEgo P39 FINISHED
Object Good Cop E74788 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: Good Cop | Statement: [Bad Cop, hasAlterEgo, Good Cop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Good Cop
Context triple: [Bad Cop, hasAlterEgo, Good Cop]
  • A. Bad Cop chosen
    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.
  • B. Bon Cop, Bad Cop
    Bon Cop, Bad Cop is a bilingual Canadian action-comedy film that pairs an Ontario and a Quebec police officer who must overcome cultural differences to solve a cross-border crime.
  • 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. COPS
    COPS is the abbreviation for the European Union’s Political and Security Committee, a key body responsible for shaping and overseeing the EU’s Common Foreign and Security Policy and crisis management operations.
  • E. Serpico
    Serpico is a 1973 crime drama film based on the true story of NYPD officer Frank Serpico, who exposed widespread police corruption.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbcc7b92481908d2d99948780f4d0 completed March 8, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb87c3748190bce62e86fcdfa380 completed March 13, 2026, 7:23 a.m.
Created at: March 8, 2026, 3:20 p.m.