Triple
T11631847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple A13 Bionic |
E276416
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | Neural Engine |
E38961
|
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: Neural Engine | Statement: [Apple A13 Bionic, supports, Neural Engine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neural Engine Context triple: [Apple A13 Bionic, supports, Neural Engine]
-
A.
NPU
NPU is a leading Chinese research university in Xi’an renowned for its strengths in aeronautics, astronautics, and marine engineering.
-
B.
NPU
NPU is the commonly used abbreviation for the National Police of Ukraine, the country’s central law enforcement agency responsible for maintaining public order and safety.
-
C.
Qualcomm AI Engine
Qualcomm AI Engine is Qualcomm’s integrated hardware–software platform for accelerating on-device artificial intelligence tasks across its mobile and embedded chipsets.
-
D.
Tensor Processing Unit
A Tensor Processing Unit (TPU) is a specialized AI accelerator chip designed by Google to efficiently perform large-scale machine learning computations, particularly for neural networks.
-
E.
Apple Neural Engine
chosen
Apple Neural Engine is Apple’s dedicated on-chip hardware accelerator designed to efficiently perform machine learning and AI computations on its devices.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25aa9188190ab13d79139f37e7e |
completed | April 10, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee87a20af481909b47775c7cb6ec3b |
completed | April 26, 2026, 9:46 p.m. |
Created at: April 8, 2026, 9:39 p.m.