Triple
T1870145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple M1 Pro |
E39014
|
entity |
| Predicate | ISA |
P637
|
FINISHED |
| Object | ARMv8-A |
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-A | Statement: [Apple M1 Pro, ISA, ARMv8-A]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ARMv8-A Context triple: [Apple M1 Pro, ISA, ARMv8-A]
-
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.
ARMv8 cryptographic extensions
ARMv8 cryptographic extensions are a set of hardware instructions in the ARMv8 architecture designed to accelerate common cryptographic operations such as AES and SHA for improved performance and security.
-
C.
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.
-
D.
Apple A14 Bionic
Apple A14 Bionic is a 5-nanometer ARM-based system-on-a-chip designed by Apple for high-performance, energy-efficient use in iPhones and iPads.
-
E.
Apple A15 Bionic
Apple A15 Bionic is a high-performance, energy-efficient system-on-a-chip used in various Apple devices, featuring advanced CPU, GPU, and neural engine components for enhanced processing and machine learning 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0b95c0c8190a37907755541f8c6 |
completed | March 7, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3ca2bd48190b055dd2e657c4dd9 |
completed | March 8, 2026, 10:10 p.m. |
Created at: March 4, 2026, 7:34 p.m.