Triple

T36409023
Position Surface form Disambiguated ID Type / Status
Subject Tate curve E896825 entity
Predicate hasUniformization P39248 FINISHED
Object rigid analytic uniformization by the multiplicative group 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: rigid analytic uniformization by the multiplicative group | Statement: [Tate curve, hasUniformization, rigid analytic uniformization by the multiplicative group]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUniformization
Context triple: [Tate curve, hasUniformization, rigid analytic uniformization by the multiplicative group]
  • A. uniformizedBy chosen
    Indicates that one entity has been made uniform, standardized, or brought into a consistent form or structure by another entity.
  • B. uniformizes
    Indicates making multiple entities or elements consistent, standardized, or uniform in form, appearance, or behavior.
  • C. isUniform
    Indicates that all elements or parts within a given set, structure, or context share the same characteristics or value.
  • D. usesUniform
    Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
  • E. requiresUniformity
    Indicates that one entity imposes a condition that another entity (or set of entities) must be consistent or identical in a specified aspect.
  • 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_69f76e54ce408190849acc3f7758937c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fd5bf69acc819092a01e4259785dc3 completed May 8, 2026, 3:43 a.m.
PD Predicate disambiguation batch_69fd59b3f4ac8190a7f9dd3142da6e09 completed May 8, 2026, 3:34 a.m.
Created at: May 3, 2026, 4:10 p.m.