Triple

T22003994
Position Surface form Disambiguated ID Type / Status
Subject Hunt E543402 entity
Predicate ageRatingInSouthKorea P135770 FINISHED
Object 15+ 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: 15+ | Statement: [Hunt, ageRatingInSouthKorea, 15+]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ageRatingInSouthKorea
Context triple: [Hunt, ageRatingInSouthKorea, 15+]
  • A. filmRatingKorea chosen
    Indicates that a film has a specific official content rating assigned by the Korean rating authority.
  • B. ageRatingContext
    Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
  • C. ratedFor
    Indicates that an entity has been evaluated and assigned a suitability or quality level for a particular purpose, context, or audience.
  • D. ageRatingSystem
    Indicates the classification scheme or standard used to assign age-appropriateness ratings to content.
  • E. juvenileRating
    Indicates that something has been evaluated and assigned a suitability or content rating specifically for juveniles or young audiences.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276cab5c8190ac1236fde7e0394a completed April 28, 2026, 9:32 p.m.
PD Predicate disambiguation batch_69e6f62dc9d88190ae387f145f9528de completed April 21, 2026, 3:59 a.m.
Created at: April 16, 2026, 8:20 p.m.