Triple

T9675010
Position Surface form Disambiguated ID Type / Status
Subject NVIDIA Triton Inference Server E234124 entity
Predicate supportsFormat P203 FINISHED
Object TensorRT engine E256947 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: TensorRT engine | Statement: [NVIDIA Triton Inference Server, supportsFormat, TensorRT engine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TensorRT engine
Context triple: [NVIDIA Triton Inference Server, supportsFormat, TensorRT engine]
  • A. NVIDIA TensorRT chosen
    NVIDIA TensorRT is a high-performance deep learning inference optimizer and runtime library designed to accelerate AI models on NVIDIA GPUs in production environments.
  • B. 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.
  • C. 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.
  • D. TensorFlow Serving
    TensorFlow Serving is a flexible, high-performance system for deploying and serving machine learning models in production, particularly those built with TensorFlow.
  • E. Tensor Processing Unit
    A Tensor Processing Unit (TPU) is a specialized AI accelerator chip designed by Google to efficiently perform large-scale machine learning computations, particularly for neural networks.
  • 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_69ca848f55e48190b3f67252571c3d45 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c6d6dd48190a77c486337a58cb6 completed April 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d190f9bf78819093542adae997a668 completed April 4, 2026, 10:30 p.m.
Created at: March 30, 2026, 8:15 p.m.