Triple

T10882142
Position Surface form Disambiguated ID Type / Status
Subject NVIDIA RAPIDS E256948 entity
Predicate component P35 FINISHED
Object cuIO
cuIO is the RAPIDS GPU-accelerated input/output library that enables fast reading and writing of data formats like CSV, Parquet, and ORC directly on NVIDIA GPUs.
 E890462 NE FINISHED

How this triple was built (4 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: cuIO | Statement: [NVIDIA RAPIDS, component, cuIO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: cuIO
Context triple: [NVIDIA RAPIDS, component, cuIO]
  • A. cuDNN
    cuDNN is NVIDIA’s GPU-accelerated library of optimized primitives for deep neural networks, widely used to speed up training and inference in frameworks like TensorFlow and PyTorch.
  • B. CU
    CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
  • C. CU
    CU is the commonly used abbreviation for the multi-campus University of Colorado public university system in the United States.
  • D. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • E. CU
    CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: cuIO
Triple: [NVIDIA RAPIDS, component, cuIO]
Generated description
cuIO is the RAPIDS GPU-accelerated input/output library that enables fast reading and writing of data formats like CSV, Parquet, and ORC directly on NVIDIA GPUs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: cuIO
Target entity description: cuIO is the RAPIDS GPU-accelerated input/output library that enables fast reading and writing of data formats like CSV, Parquet, and ORC directly on NVIDIA GPUs.
  • A. cuDNN
    cuDNN is NVIDIA’s GPU-accelerated library of optimized primitives for deep neural networks, widely used to speed up training and inference in frameworks like TensorFlow and PyTorch.
  • B. CU
    CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
  • C. CU
    CU is the commonly used abbreviation for the multi-campus University of Colorado public university system in the United States.
  • D. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • E. CU
    CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
  • F. None of above. chosen

Provenance (5 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751da559c819094c3680a9f734ee7 completed April 9, 2026, 7:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7e479cc81909fb8510364d6fc0e completed April 15, 2026, 8:41 p.m.
NEDg Description generation batch_69e002709d38819099c4402d30824612 completed April 15, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_69e005873ba48190b8c24c77611562fa completed April 15, 2026, 9:39 p.m.
Created at: April 8, 2026, 9:21 p.m.