Triple

T20627138
Position Surface form Disambiguated ID Type / Status
Subject Radon’s theorem E506848 entity
Predicate hasGeneralization P2372 FINISHED
Object colorful Radon theorem NE NERFINISHED

How this triple was built (3 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: colorful Radon theorem | Statement: [Radon’s theorem, hasGeneralization, colorful Radon theorem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: colorful Radon theorem
Context triple: [Radon’s theorem, hasGeneralization, colorful Radon theorem]
  • A. Radon’s theorem
    Radon’s theorem is a fundamental result in convex geometry stating that any set of sufficiently many points in Euclidean space can be partitioned into two disjoint subsets whose convex hulls intersect.
  • B. Tverberg’s theorem
    Tverberg’s theorem is a fundamental result in combinatorial geometry that guarantees any sufficiently large set of points in Euclidean space can be partitioned into subsets whose convex hulls all intersect.
  • C. colorful Helly theorem
    The colorful Helly theorem is a combinatorial geometric result that generalizes Helly’s theorem by asserting intersection properties for families of convex sets partitioned into color classes.
  • D. Helly’s theorem
    Helly’s theorem is a fundamental result in convex geometry that gives conditions under which a family of convex sets in Euclidean space has a nonempty common intersection.
  • E. Sylvester–Gallai theorem
    The Sylvester–Gallai theorem is a result in incidence geometry stating that for any finite set of points in the Euclidean plane not all on a single line, there exists a line that passes through exactly two of the points.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: colorful Radon theorem
Target entity description: The colorful Radon theorem is a combinatorial result in discrete geometry that extends Radon’s theorem by guaranteeing a partition with intersecting convex hulls when points are chosen from several differently “colored” sets.
  • A. Radon’s theorem
    Radon’s theorem is a fundamental result in convex geometry stating that any set of sufficiently many points in Euclidean space can be partitioned into two disjoint subsets whose convex hulls intersect.
  • B. Tverberg’s theorem
    Tverberg’s theorem is a fundamental result in combinatorial geometry that guarantees any sufficiently large set of points in Euclidean space can be partitioned into subsets whose convex hulls all intersect.
  • C. colorful Helly theorem chosen
    The colorful Helly theorem is a combinatorial geometric result that generalizes Helly’s theorem by asserting intersection properties for families of convex sets partitioned into color classes.
  • D. Helly’s theorem
    Helly’s theorem is a fundamental result in convex geometry that gives conditions under which a family of convex sets in Euclidean space has a nonempty common intersection.
  • E. Sylvester–Gallai theorem
    The Sylvester–Gallai theorem is a result in incidence geometry stating that for any finite set of points in the Euclidean plane not all on a single line, there exists a line that passes through exactly two of the points.
  • F. None of above.

Provenance (2 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.
Created at: April 16, 2026, 11:42 a.m.