Triple

T25822390
Position Surface form Disambiguated ID Type / Status
Subject Severe Threat Level E650436 entity
Predicate scaleMembers P160288 FINISHED
Object Severe Threat 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: Severe Threat Level | Statement: [Severe Threat Level, scaleMembers, Severe Threat Level]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: scaleMembers
Context triple: [Severe Threat Level, scaleMembers, Severe Threat Level]
  • A. scaleMembers chosen
    Indicates adjusting the size, number, or magnitude of members in a group or collection according to some scaling factor or rule.
  • B. scaleProperty
    Indicates that one entity defines or modifies the scale, magnitude, or proportional sizing used to interpret or represent a property of another entity.
  • C. scaleRelation
    Indicates a relationship where one quantity, object, or representation is proportionally larger or smaller than another according to a specific scale or factor.
  • D. scaleFunction
    Indicates a relationship where one entity defines how another entity’s values are proportionally adjusted or transformed according to a scaling rule or factor.
  • E. scalingProperty
    Indicates how a quantity or behavior changes in proportion to changes in another variable, typically under resizing or rescaling conditions.
  • 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_69e7ab367fcc8190a5ff1e7f3da046a4 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f61f12b0f08190bc4a16907941864c completed May 2, 2026, 3:58 p.m.
PD Predicate disambiguation batch_69f61b37a5648190b10d33ae205ccfee completed May 2, 2026, 3:41 p.m.
Created at: April 22, 2026, 7:30 a.m.