Triple

T20165246
Position Surface form Disambiguated ID Type / Status
Subject Ricoh 2A03 E491810 entity
Predicate integratesFunction P13995 FINISHED
Object CPU NE NERFINISHED

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: CPU | Statement: [Ricoh 2A03, integratesFunction, CPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CPU
Context triple: [Ricoh 2A03, integratesFunction, CPU]
  • A. CPU chosen
    A CPU (Central Processing Unit) is the primary component of a computer that performs most of the processing and executes instructions for programs and operating systems.
  • B. CPU
    The Communist Party of Ukraine is a left-wing political party that was the ruling party in Soviet Ukraine and later operated in independent Ukraine until it was banned.
  • C. 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.
  • D. GPU
    GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e668442d2c81908bb1a0fac9895b5e completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.