Triple
T17035322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tucker decomposition |
E413306
|
entity |
| Predicate | optimizationFormulation |
P3660
|
FINISHED |
| Object | least-squares minimization |
—
|
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: least-squares minimization | Statement: [Tucker decomposition, optimizationFormulation, least-squares minimization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optimizationFormulation Context triple: [Tucker decomposition, optimizationFormulation, least-squares minimization]
-
A.
exampleFormulation
Indicates that one entity serves as a representative or illustrative formulation or expression of another entity.
-
B.
optimizationSolver
Indicates a relationship where a solver entity is used to compute an optimal solution for a given optimization problem or task.
-
C.
mathematicallyFormulatedIn
Indicates that something is expressed, defined, or represented using mathematical formulas, equations, or formal mathematical structures within a given context.
-
D.
hasEquivalentFormulation
Indicates that two representations, statements, or formulations express the same underlying meaning, condition, or effect, even if they differ in form.
-
E.
hasFormulation
chosen
Indicates that one entity is expressed, prepared, or configured in a particular form or composition defined by another entity.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f05824819091d2aa02e5591e26 |
completed | April 18, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.