Triple

T20627124
Position Surface form Disambiguated ID Type / Status
Subject Radon’s theorem E506848 entity
Predicate minimumNumberOfPoints P26954 FINISHED
Object d+2 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: d+2 | Statement: [Radon’s theorem, minimumNumberOfPoints, d+2]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: minimumNumberOfPoints
Context triple: [Radon’s theorem, minimumNumberOfPoints, d+2]
  • A. minimumNumber chosen
    Indicates that the associated value is the smallest or least quantity allowed, required, or observed within a given set or context.
  • B. hasNumberOfPoints
    Indicates that an entity is associated with a specific count of points it possesses or comprises.
  • C. minimumCircuitsRequired
    Indicates the smallest number of circuits that must be present or used for a given system, configuration, or requirement to be satisfied.
  • D. minimumDegree
    Indicates that the relationship specifies the smallest number of connections or edges incident to any entity within a given structure or set.
  • E. minimumRange
    Indicates the smallest allowable or observed value within a specified range for a given relationship or measurement.
  • 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_69e0b4bd4a0081908d4e97a590a33fb2 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe576c081909231dc0d7304b9a9 completed April 20, 2026, 10:42 p.m.
PD Predicate disambiguation batch_69e5a00c43308190b7ea58d559257e07 completed April 20, 2026, 3:39 a.m.
Created at: April 16, 2026, 11:42 a.m.