Triple
T22444825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | illumos |
E554837
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | SPARC architecture |
—
|
NE NERFINISHED |
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: SPARC architecture | Statement: [illumos, supports, SPARC architecture]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SPARC architecture Context triple: [illumos, supports, SPARC architecture]
-
A.
SPARC microprocessor architecture
chosen
The SPARC microprocessor architecture is a RISC-based instruction set architecture widely used in high-performance and enterprise servers, originally created to power scalable, multi-processor systems.
-
B.
SPARC
SPARC is a core project of the World Climate Research Programme that focuses on understanding the role of the stratosphere and upper troposphere in the Earth’s climate system.
-
C.
SPARC V9
SPARC V9 is a 64-bit RISC instruction set architecture developed by Sun Microsystems for high-performance, scalable SPARC processors.
-
D.
RISC architecture
RISC architecture is a CPU design philosophy that uses a small, highly optimized set of simple instructions to achieve high performance and efficiency.
-
E.
SPARC64 X
SPARC64 X is a 64-bit SPARC microprocessor developed by Fujitsu for high-performance enterprise and server computing workloads.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae517208190924a7968723f55ef |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.