Triple
T8414863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NEON SIMD |
E198707
|
entity |
| Predicate | distinctFrom |
P1612
|
FINISHED |
| Object | x86 AVX |
E163100
|
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: x86 AVX | Statement: [NEON SIMD, distinctFrom, x86 AVX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: x86 AVX Context triple: [NEON SIMD, distinctFrom, x86 AVX]
-
A.
Intel AVX
chosen
Intel AVX is an x86 processor instruction set extension from Intel that accelerates floating-point and vector-intensive workloads, commonly used in high-performance computing, multimedia, and scientific applications.
-
B.
Intel AVX2
Intel AVX2 is an x86 instruction set extension from Intel that enhances performance for integer-heavy and vectorized workloads through wider SIMD operations and new vector instructions.
-
C.
AVX-512
AVX-512 is an advanced SIMD instruction set for x86 processors that enables high-throughput parallel processing using 512-bit wide vector operations.
-
D.
AMD-V
AMD-V is AMD’s hardware-assisted virtualization technology that enables efficient and secure running of virtual machines on compatible processors.
-
E.
V (vector extension)
V (vector extension) is the RISC-V standard for scalable vector processing, enabling efficient parallel computation on variable-length data vectors.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e443a08190983d9a0a61e0f781 |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce032a25ec819094c6346eb2a7f973 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:06 p.m.