Triple

T10882098
Position Surface form Disambiguated ID Type / Status
Subject NVIDIA TensorRT E256947 entity
Predicate integratesWith P1075 FINISHED
Object ONNX Runtime E814638 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: ONNX Runtime | Statement: [NVIDIA TensorRT, integratesWith, ONNX Runtime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ONNX Runtime
Context triple: [NVIDIA TensorRT, integratesWith, ONNX Runtime]
  • A. ONNX Runtime chosen
    ONNX Runtime is a high-performance, cross-platform inference engine for running machine learning models in the Open Neural Network Exchange (ONNX) format across a variety of hardware and deployment environments.
  • B. ONNX
    ONNX (Open Neural Network Exchange) is an open standard format for representing machine learning models that enables interoperability between different deep learning frameworks and tools.
  • C. NVIDIA TensorRT
    NVIDIA TensorRT is a high-performance deep learning inference optimizer and runtime library designed to accelerate AI models on NVIDIA GPUs in production environments.
  • D. NVIDIA Triton Inference Server
    NVIDIA Triton Inference Server is an open-source, production-ready platform for serving and scaling AI model inference across GPUs and CPUs with support for multiple frameworks and deployment environments.
  • E. OpenVINO
    OpenVINO is an open-source toolkit from Intel for optimizing and deploying deep learning inference across a range of hardware platforms, especially Intel CPUs, integrated GPUs, VPUs, and FPGAs.
  • 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_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_69e154e49ab08190b522b5361ac65c01 completed April 16, 2026, 9:30 p.m.
Created at: April 8, 2026, 9:21 p.m.