Triple

T8822716
Position Surface form Disambiguated ID Type / Status
Subject NVIDIA Jetson embedded modules E209944 entity
Predicate supports P516 FINISHED
Object TensorRT 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 | Statement: [NVIDIA Jetson embedded modules, supports, TensorRT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TensorRT
Context triple: [NVIDIA Jetson embedded modules, supports, TensorRT]
  • 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. PyTorch
    PyTorch is an open-source deep learning framework widely used for building and training neural networks, known for its dynamic computation graph and strong support for research and production in Python.
  • 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_69ca8364e13081909c85fe80f44fe86f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc602ed87c8190ab772e5cbb2da68d completed April 1, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_69cf6fd3b3348190a63bfd29860cc95f completed April 3, 2026, 7:44 a.m.
Created at: March 30, 2026, 6:46 p.m.