Triple

T14314135
Position Surface form Disambiguated ID Type / Status
Subject Bernstein set E354908 entity
Predicate intersectionProperty P102344 FINISHED
Object meets every uncountable closed subset of R in at least one point 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: meets every uncountable closed subset of R in at least one point | Statement: [Bernstein set, intersectionProperty, meets every uncountable closed subset of R in at least one point]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: intersectionProperty
Context triple: [Bernstein set, intersectionProperty, meets every uncountable closed subset of R in at least one point]
  • A. fieldIntersection
    Indicates that two or more fields or domains share a common overlapping area or set of elements.
  • B. intersectionRole
    Indicates a role or function that an entity specifically holds at the point where two or more entities, paths, or sets intersect.
  • C. isIntersectionOf chosen
    Indicates that something is the exact common part shared by two or more other things, typically where they overlap or meet.
  • D. servesIntersection
    Indicates that one entity provides service or operational coverage to a specific road or transit intersection.
  • E. hasNotableIntersection
    Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b49e5481909b9ffab2d922e284 completed April 14, 2026, 6:21 p.m.
PD Predicate disambiguation batch_69de2a9515f4819081aabf251bca5878 completed April 14, 2026, 11:52 a.m.
Created at: April 10, 2026, 1:12 a.m.