Triple

T16574843
Position Surface form Disambiguated ID Type / Status
Subject Mikhail Gromov E402682 entity
Predicate notableFor P22 FINISHED
Object Gromov–Hausdorff distance
The Gromov–Hausdorff distance is a metric that quantifies how far apart two compact metric spaces are from being isometric, playing a central role in modern metric geometry and geometric group theory.
E1223058 NE FINISHED

How this triple was built (4 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: Gromov–Hausdorff distance | Statement: [Mikhail Gromov, notableFor, Gromov–Hausdorff distance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gromov–Hausdorff distance
Context triple: [Mikhail Gromov, notableFor, Gromov–Hausdorff distance]
  • A. Hausdorff metric
    The Hausdorff metric is a distance function that measures how far two subsets of a metric space are from each other, widely used in topology, geometry, and shape analysis.
  • B. Banach–Mazur distance
    The Banach–Mazur distance is a numerical measure in functional analysis that quantifies how "far apart" two finite-dimensional normed vector spaces are up to linear isomorphism.
  • C. Cheeger–Gromov compactness theorem
    The Cheeger–Gromov compactness theorem is a fundamental result in Riemannian geometry that gives conditions under which a sequence of Riemannian manifolds has a subsequence converging (in the Gromov–Hausdorff or smooth sense) to a limit space.
  • D. Hausdorff measure
    Hausdorff measure is a fundamental concept in geometric measure theory that generalizes the notion of length, area, and volume to sets with arbitrary fractal or irregular structure in metric spaces.
  • E. Metric Structures for Riemannian and Non-Riemannian Spaces
    "Metric Structures for Riemannian and Non-Riemannian Spaces" is a foundational monograph by Mikhail Gromov that systematically develops the theory of metric spaces and its applications to Riemannian geometry, geometric group theory, and global analysis.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gromov–Hausdorff distance
Triple: [Mikhail Gromov, notableFor, Gromov–Hausdorff distance]
Generated description
The Gromov–Hausdorff distance is a metric that quantifies how far apart two compact metric spaces are from being isometric, playing a central role in modern metric geometry and geometric group theory.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gromov–Hausdorff distance
Target entity description: The Gromov–Hausdorff distance is a metric that quantifies how far apart two compact metric spaces are from being isometric, playing a central role in modern metric geometry and geometric group theory.
  • A. Hausdorff metric
    The Hausdorff metric is a distance function that measures how far two subsets of a metric space are from each other, widely used in topology, geometry, and shape analysis.
  • B. Banach–Mazur distance
    The Banach–Mazur distance is a numerical measure in functional analysis that quantifies how "far apart" two finite-dimensional normed vector spaces are up to linear isomorphism.
  • C. Cheeger–Gromov compactness theorem
    The Cheeger–Gromov compactness theorem is a fundamental result in Riemannian geometry that gives conditions under which a sequence of Riemannian manifolds has a subsequence converging (in the Gromov–Hausdorff or smooth sense) to a limit space.
  • D. Hausdorff measure
    Hausdorff measure is a fundamental concept in geometric measure theory that generalizes the notion of length, area, and volume to sets with arbitrary fractal or irregular structure in metric spaces.
  • E. Metric Structures for Riemannian and Non-Riemannian Spaces
    "Metric Structures for Riemannian and Non-Riemannian Spaces" is a foundational monograph by Mikhail Gromov that systematically develops the theory of metric spaces and its applications to Riemannian geometry, geometric group theory, and global analysis.
  • F. None of above. chosen

Provenance (5 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3595bbbbc8190b023f4872908c031 completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007595cfd08190bae54d29427a1d3c completed May 10, 2026, 12:09 p.m.
NEDg Description generation batch_6a00796f21c481908a41ffc7658bd0e4 completed May 10, 2026, 12:26 p.m.
NED2 Entity disambiguation (via description) batch_6a007a14bfb481908cf94bfcde7d9de4 completed May 10, 2026, 12:29 p.m.
Created at: April 10, 2026, 5:16 a.m.