Triple

T3536715
Position Surface form Disambiguated ID Type / Status
Subject Bad Cop E74788 entity
Predicate targetAudienceContext P10804 FINISHED
Object family film character LITERAL 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: family film character | Statement: [Bad Cop, targetAudienceContext, family film character]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetAudienceContext
Context triple: [Bad Cop, targetAudienceContext, family film character]
  • A. targetMarket
    Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
  • B. typicalAudience chosen
    Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
  • C. contextOf
    Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
  • D. marketContext
    Indicates the broader economic, competitive, and situational conditions under which a product, service, or transaction is positioned or evaluated.
  • E. context
    Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
  • F. None of above.

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.
PD Predicate disambiguation batch_69adae13ab808190a5d6ecdc7543445e completed March 8, 2026, 5:12 p.m.
Created at: March 8, 2026, 3:20 p.m.