Triple

T106499
Position Surface form Disambiguated ID Type / Status
Subject Union Pacific Railroad E2147 entity
Predicate safetyFocus P31 FINISHED
Object Positive Train Control implementation 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: Positive Train Control implementation | Statement: [Union Pacific Railroad, safetyFocus, Positive Train Control implementation]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: safetyFocus
Context triple: [Union Pacific Railroad, safetyFocus, Positive Train Control implementation]
  • A. focusesOn chosen
    Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
  • B. securityFeature
    Indicates that an entity provides, embodies, or is associated with a mechanism or property intended to enhance safety, protection, or defense against threats or vulnerabilities.
  • C. protects
    Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
  • D. security
    Indicates that an entity provides protection, safety measures, or safeguards to another entity or against specific threats or risks.
  • E. awareness
    Indicates that an entity has conscious knowledge, perception, or understanding of another entity, situation, or fact.
  • 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_69a24e0a5b7c81908d52da08c60dabc4 completed Feb. 28, 2026, 2:08 a.m.
NER Named-entity recognition batch_69a256ec650c8190bee2067e37065527 completed Feb. 28, 2026, 2:46 a.m.
PD Predicate disambiguation batch_69a2563d33788190999d471b486d5603 completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:12 a.m.