Triple

T31667
Position Surface form Disambiguated ID Type / Status
Subject Nash embedding theorem E631 entity
Predicate clarifies P264 FINISHED
Object relationship between intrinsic curvature and extrinsic curvature 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: relationship between intrinsic curvature and extrinsic curvature | Statement: [Nash embedding theorem, clarifies, relationship between intrinsic curvature and extrinsic curvature]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: clarifies
Context triple: [Nash embedding theorem, clarifies, relationship between intrinsic curvature and extrinsic curvature]
  • A. advises
    Indicates that one entity provides guidance, recommendations, or counsel to another entity.
  • B. describes chosen
    Indicates that one entity provides an explanation, representation, or account of another entity or concept.
  • C. separates
    Indicates that one entity divides, parts, or keeps other entities apart from each other.
  • D. implies
    Indicates that the truth of one statement guarantees or leads logically to the truth of another statement.
  • E. establishes
    Indicates that one entity initiates, creates, or formally sets up another entity, relationship, or state, often giving it official or recognized status.
  • 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_69a2479dec388190967ba648663442c9 completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a249ec0d288190ac3a0939db61813b completed Feb. 28, 2026, 1:50 a.m.
PD Predicate disambiguation batch_69a24870417081909c7c01e400c94716 completed Feb. 28, 2026, 1:44 a.m.
Created at: Feb. 28, 2026, 1:44 a.m.