Triple

T13212812
Position Surface form Disambiguated ID Type / Status
Subject Kimura lock E314534 entity
Predicate trainingConsideration P108547 FINISHED
Object must be applied slowly to avoid injury 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: must be applied slowly to avoid injury | Statement: [Kimura lock, trainingConsideration, must be applied slowly to avoid injury]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: trainingConsideration
Context triple: [Kimura lock, trainingConsideration, must be applied slowly to avoid injury]
  • A. training
    Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
  • B. trainingUnder
    Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
  • C. trainingUse
    Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
  • D. trainingEmphasized
    Indicates that particular training or instructional activities are given special focus, priority, or importance within a broader context or process.
  • E. trainingComponent
    Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
  • F. None of above. chosen

Provenance (4 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9f0f148190a0698ef27573c885 completed April 10, 2026, 11:49 p.m.
PD Predicate disambiguation batch_69d98bc938f081909f123bdf1263ff7f completed April 10, 2026, 11:46 p.m.
PDg Predicate description generation batch_69d98c959ba08190adf29dc0c4e1fca6 completed April 10, 2026, 11:49 p.m.
Created at: April 9, 2026, 9:17 p.m.