Triple

T32930813
Position Surface form Disambiguated ID Type / Status
Subject United Nations Decade of Action for Road Safety E842393 entity
Predicate addressesRiskFactor P28689 FINISHED
Object speeding 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: speeding | Statement: [United Nations Decade of Action for Road Safety, addressesRiskFactor, speeding]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: addressesRiskFactor
Context triple: [United Nations Decade of Action for Road Safety, addressesRiskFactor, speeding]
  • A. riskAddressed chosen
    Indicates that a particular risk has been identified and is being mitigated, managed, or otherwise handled by an associated action, control, or measure.
  • B. hasRiskFactorFor
    Indicates that one entity contributes to or increases the likelihood of another entity experiencing a particular risk or adverse outcome.
  • C. hasRiskFrom
    Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
  • D. riskElement
    Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
  • E. riskFeature
    Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
  • 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_69f34948adfc8190a937f1f622783c0b completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6f8164698819090c1b471f1caa4c6 completed May 3, 2026, 7:24 a.m.
PD Predicate disambiguation batch_69f6f6619404819084662aef1238261c completed May 3, 2026, 7:16 a.m.
Created at: May 1, 2026, 1:20 a.m.