Triple

T6334213
Position Surface form Disambiguated ID Type / Status
Subject TARS E142450 entity
Predicate safetySetting P70917 FINISHED
Object Configurable honesty level 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: Configurable honesty level | Statement: [TARS, safetySetting, Configurable honesty level]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: safetySetting
Context triple: [TARS, safetySetting, Configurable honesty level]
  • A. safetyRequirement
    Indicates that one entity specifies or imposes conditions, standards, or measures necessary to ensure the safety of another entity or activity.
  • B. safetyFunction
    Indicates that one entity serves as a safety-related function or mechanism that protects, safeguards, or reduces risk for another entity or process.
  • C. safety
    Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
  • D. safetyExpectation
    Indicates an expected level or standard of safety that should be maintained or provided in a given context or relationship.
  • E. safetyGoal
    Indicates that an entity is associated with a specific safety objective or target condition intended to prevent harm or reduce risk.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06549084c8190b73fd94c9e0cb302 completed March 22, 2026, 9:55 p.m.
PD Predicate disambiguation batch_69c060e7e2d48190af9d004236466788 completed March 22, 2026, 9:36 p.m.
PDg Predicate description generation batch_69c064c080148190a7c3218867f1f572 completed March 22, 2026, 9:53 p.m.
Created at: March 22, 2026, 4:30 p.m.