Triple

T21021185
Position Surface form Disambiguated ID Type / Status
Subject Afterburn E517809 entity
Predicate hasRestraint P22102 FINISHED
Object seat belt 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: seat belt | Statement: [Afterburn, hasRestraint, seat belt]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRestraint
Context triple: [Afterburn, hasRestraint, seat belt]
  • A. restraintType chosen
    Indicates the specific kind or method of restraint applied in a given situation or relationship.
  • B. usesRestraints
    Indicates that one entity applies or employs physical or procedural restraints on another entity.
  • C. restraintPurpose
    Indicates that one entity is used to restrain another entity for a specific purpose or intended outcome.
  • D. restraintManufacturer
    Indicates that one entity is the manufacturer or producer of a restraint device used to limit or control another entity.
  • E. hadRestrictionsOn
    Indicates that one entity imposed or was subject to specific limitations, rules, or constraints regarding another entity or activity.
  • 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_69e0b50262b081909bc488937145eb73 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc5db0b88190ae61ea8b38e8ecf7 completed April 21, 2026, 4:26 a.m.
PD Predicate disambiguation batch_69e5dbf274ac81909bbf245627dc8fdc completed April 20, 2026, 7:55 a.m.
Created at: April 16, 2026, 1:54 p.m.