Triple
T15860298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schmidt orthogonalization |
E384564
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | modified Gram–Schmidt process |
E384564
|
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: modified Gram–Schmidt process | Statement: [Schmidt orthogonalization, hasVariant, modified Gram–Schmidt process]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: modified Gram–Schmidt process Context triple: [Schmidt orthogonalization, hasVariant, modified Gram–Schmidt process]
-
A.
Schmidt orthogonalization
chosen
Schmidt orthogonalization is a mathematical procedure, also known as the Gram–Schmidt process, that converts a set of linearly independent vectors into an orthonormal set spanning the same subspace.
-
B.
Bartels–Stewart algorithm
The Bartels–Stewart algorithm is a numerical linear algebra method that efficiently solves certain matrix equations, particularly Sylvester and Lyapunov equations, using Schur decompositions.
-
C.
Lanczos algorithm
The Lanczos algorithm is an iterative numerical method used to approximate eigenvalues and eigenvectors of large sparse matrices, particularly in scientific computing and numerical linear algebra.
-
D.
Jacobi eigenvalue algorithm
The Jacobi eigenvalue algorithm is an iterative numerical method for computing all eigenvalues and eigenvectors of a real symmetric matrix by applying a sequence of orthogonal similarity transformations.
-
E.
Schmidt decomposition
The Schmidt decomposition is a mathematical technique in functional analysis and quantum information theory that expresses a bipartite vector (such as a quantum state) as a sum of orthogonal product states with nonnegative coefficients, revealing its entanglement structure.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555a1f008190bb3f03b0f35ed8a4 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa14da7ac8190bbef49a1602a76fe |
completed | May 9, 2026, 9:04 p.m. |
Created at: April 10, 2026, 4:50 a.m.