Triple
T576669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARM |
E13771
|
entity |
| Predicate | hasVersion |
P455
|
FINISHED |
| Object | ARMv8 |
E13771
|
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: ARMv8 | Statement: [ARM, hasVersion, ARMv8]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ARMv8 Context triple: [ARM, hasVersion, ARMv8]
-
A.
ARM
chosen
ARM is a family of energy-efficient RISC processor architectures widely used in mobile devices, embedded systems, and increasingly in laptops and servers.
-
B.
RISC-V
RISC-V is an open, extensible instruction set architecture (ISA) based on the reduced instruction set computing (RISC) principles, widely used for research, embedded systems, and increasingly general-purpose computing.
-
C.
AltiVec
AltiVec is a vector processing extension for the PowerPC architecture that accelerates multimedia, signal processing, and other parallelizable computations.
-
D.
Apple A12Z Bionic
Apple A12Z Bionic is an ARM-based system-on-a-chip designed by Apple, notable for powering the 2020 iPad Pro with enhanced CPU and GPU performance for demanding mobile and creative workloads.
-
E.
Apple A16 Bionic
Apple A16 Bionic is a high-performance, energy-efficient system-on-a-chip used in recent iPhone models, featuring advanced CPU, GPU, and neural engine capabilities for demanding mobile tasks.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b68cc808190b1ba45bdad78443d |
completed | March 1, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4ff4db0248190b2b3ca0290467313 |
completed | March 2, 2026, 3:09 a.m. |
Created at: March 1, 2026, 7:33 p.m.