Triple

T5020088
Position Surface form Disambiguated ID Type / Status
Subject Genrikh Yagoda E112828 entity
Predicate memberOf P10 FINISHED
Object GPU E85097 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: [Genrikh Yagoda, memberOf, GPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GPU
Context triple: [Genrikh Yagoda, memberOf, GPU]
  • A. GPU chosen
    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
    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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7342c62881909acb35849da8761c completed March 20, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be927f4ad0819096826f6cb141c90b completed March 21, 2026, 12:43 p.m.
Created at: March 20, 2026, 1:36 p.m.