Triple
T10068648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cuSPARSE |
E213160
|
entity |
| Predicate | supportsMatrixFormat |
P80839
|
FINISHED |
| Object | CSC (Compressed Sparse Column) |
E440652
|
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: CSC (Compressed Sparse Column) | Statement: [cuSPARSE, supportsMatrixFormat, CSC (Compressed Sparse Column)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CSC (Compressed Sparse Column) Context triple: [cuSPARSE, supportsMatrixFormat, CSC (Compressed Sparse Column)]
-
A.
CSR (Compressed Sparse Row)
CSR (Compressed Sparse Row) is a memory-efficient sparse matrix storage format that stores only nonzero elements and their indices in row-major order to enable fast arithmetic and matrix–vector operations.
-
B.
SparseMatrixCSC
chosen
SparseMatrixCSC is a Julia data type representing sparse matrices stored in compressed sparse column (CSC) format for efficient memory use and linear algebra operations.
-
C.
SparseArrays
SparseArrays is a Julia standard library module that provides data structures and operations for efficiently working with sparse matrices and related linear algebra.
-
D.
Cauchy matrix
A Cauchy matrix is a structured matrix whose entries are defined by the reciprocals of pairwise differences of two sequences, widely used in numerical analysis, interpolation, and algebra.
-
E.
Optimized Row Columnar
Optimized Row Columnar (ORC) is a highly efficient, columnar storage file format commonly used in big data systems like Apache Hive to enable fast query performance and effective data compression.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff8d9c08190bc030f1dcc696310 |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b63d13fc8190bdeac3c7b2529052 |
completed | April 5, 2026, 7:21 p.m. |
Created at: March 30, 2026, 8:58 p.m.