Triple
T13894014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadamard inequality |
E334041
|
entity |
| Predicate | usesNorm |
P22982
|
FINISHED |
| Object | Euclidean norm |
E121352
|
NE FINISHED |
How this triple was built (3 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: Euclidean norm | Statement: [Hadamard inequality, usesNorm, Euclidean norm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Euclidean norm Context triple: [Hadamard inequality, usesNorm, Euclidean norm]
-
A.
Euclidean metric
chosen
The Euclidean metric is the standard distance function on Euclidean space, defined by the square root of the sum of squared coordinate differences between two points.
-
B.
Euclidean space
Euclidean space is the standard flat, n-dimensional geometric setting of classical geometry and vector calculus, characterized by straight lines, right angles, and the usual distance and dot product.
-
C.
Bombieri norm
The Bombieri norm is a mathematical norm on polynomials, introduced by Enrico Bombieri, that is particularly useful in analytic number theory and the study of polynomial inequalities.
-
D.
Chebyshev distance (L-infinity metric)
Chebyshev distance (L-infinity metric) is a distance measure on a grid or in n-dimensional space defined as the maximum absolute difference along any coordinate axis between two points.
-
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNorm Context triple: [Hadamard inequality, usesNorm, Euclidean norm]
-
A.
hasNorm
chosen
Indicates that an entity is associated with, governed by, or characterized through a particular norm, rule, or standard.
-
B.
normIs
Indicates that something conforms to, or is characterized by, a particular standard, rule, or norm.
-
C.
normativeFor
Indicates that something establishes, prescribes, or encodes the norms, standards, or rules that should govern another thing’s behavior or state.
-
D.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
-
E.
normativelyIncludes
Indicates that one norm or rule encompasses, subsumes, or otherwise includes another within its prescribed scope or requirements.
- F. None of above.
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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a741908190bdf46d76c5f1411a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71ca8a881908ac02687fbfe62fb |
completed | May 3, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.