Triple

T11961295
Position Surface form Disambiguated ID Type / Status
Subject Lebesgue measure E284674 entity
Predicate isInnerRegularOnOpenSets P102505 FINISHED
Object true 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: true | Statement: [Lebesgue measure, isInnerRegularOnOpenSets, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isInnerRegularOnOpenSets
Context triple: [Lebesgue measure, isInnerRegularOnOpenSets, true]
  • A. isClosedAndNowhereDense
    Indicates that a set is both closed (contains all its limit points) and nowhere dense (its closure has empty interior, so it is "small" in the topological sense).
  • B. areRegularIn
    Indicates that entities participate in or occur within a context, pattern, or structure in a consistent, uniform, and rule-governed manner.
  • C. isNowhereDenseIn
    Indicates that one set is so sparse within another space that its closure has empty interior, meaning it does not contain any nontrivial open subset of that space.
  • D. isNowhereDense
    Indicates that a set is so sparse in the space that the closure of the set has empty interior, meaning it contains no nontrivial open subset.
  • E. irreducibleClosedSetsCorrespondTo
    Indicates that there is a correspondence between irreducible closed sets and another class of objects (typically points or prime ideals) in a given topological or algebraic structure.
  • F. None of above. chosen

Provenance (4 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9036941948190b150369094551731 completed April 10, 2026, 2:04 p.m.
PD Predicate disambiguation batch_69d8bb40f30c8190a0e0719bd67542bf completed April 10, 2026, 8:56 a.m.
PDg Predicate description generation batch_69d8dd0ba0f88190b7d5e358c27ca184 completed April 10, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:45 p.m.