Triple

T8414994
Position Surface form Disambiguated ID Type / Status
Subject Apple Neural Engine E198710 entity
Predicate integratedWith P2830 FINISHED
Object GPU E426676 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: GPU | Statement: [Apple Neural Engine, integratedWith, GPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GPU
Context triple: [Apple Neural Engine, integratedWith, GPU]
  • A. GPU
    The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
  • B. GPU
    GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
  • C. GPU chosen
    A GPU (Graphics Processing Unit) is a highly parallel processor originally designed for rendering graphics that is now widely used to accelerate compute-intensive tasks such as machine learning, scientific simulations, and video processing.
  • D. GPUS
    GPUS is a progressive U.S. political party focused on environmentalism, social justice, grassroots democracy, and nonviolence.
  • E. NVIDIA CUDA
    NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
  • 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.