Triple
T22813715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TMVA |
E565047
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | multivariate data analysis toolkit |
C3818
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: multivariate data analysis toolkit Context triple: [TMVA, instanceOf, multivariate data analysis toolkit]
-
A.
multivariate dependence measure
A multivariate dependence measure is a quantitative function that assesses the strength and structure of statistical relationships among multiple random variables simultaneously, beyond simple pairwise associations.
-
B.
computational analysis toolset
chosen
A computational analysis toolset is an integrated collection of software tools, libraries, and frameworks designed to process, analyze, and interpret data through algorithmic and statistical methods.
-
C.
collaborative data science platform
A collaborative data science platform is an integrated environment where multiple users can jointly develop, run, and share data workflows, analyses, and models using shared datasets, tools, and computational resources.
-
D.
framework for tensor analysis
A framework for tensor analysis is a structured system of concepts, operations, and tools that enables the representation, manipulation, and interpretation of multi-dimensional data using tensor algebra and related computational methods.
-
E.
statistical software interface
A statistical software interface is the user-facing layer that enables users to input data, specify analyses, run statistical procedures, and visualize results through graphical controls, command syntax, or APIs.
- F. None of above.
Provenance (1 batch)
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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 17, 2026, 3:32 p.m.