Triple
T6660388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felix Hausdorff |
E151458
|
entity |
| Predicate | notableConcept |
P201
|
FINISHED |
| Object | Hausdorff dimension |
E608814
|
NE 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: Hausdorff dimension | Statement: [Felix Hausdorff, notableConcept, Hausdorff dimension]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hausdorff dimension Context triple: [Felix Hausdorff, notableConcept, Hausdorff dimension]
-
A.
Hausdorff dimension
chosen
The Hausdorff dimension is a mathematical concept in fractal geometry and measure theory that generalizes the notion of dimension to capture the scaling complexity of irregular sets.
-
B.
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.
-
C.
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.
-
D.
Cantor set
The Cantor set is a classic fractal subset of the real line formed by repeatedly removing the open middle third of intervals, notable for being uncountable, perfect, nowhere dense, and having zero Lebesgue measure.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b071cc6c81909d7df1841c645661 |
completed | March 27, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f79a08548190907ea5244026b4e1 |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:02 p.m.