Triple

T18016745
Position Surface form Disambiguated ID Type / Status
Subject Google Cloud TPU v2 E431014 entity
Predicate supportsFramework P9089 FINISHED
Object PyTorch (via XLA / integration layers) 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: PyTorch (via XLA / integration layers) | Statement: [Google Cloud TPU v2, supportsFramework, PyTorch (via XLA / integration layers)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PyTorch (via XLA / integration layers)
Context triple: [Google Cloud TPU v2, supportsFramework, PyTorch (via XLA / integration layers)]
  • A. 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.
  • B. TPUs (via XLA integrations) chosen
    TPUs (via XLA integrations) are Google's specialized tensor processing units that can be used as accelerators for PyTorch models through the XLA compilation framework.
  • C. TensorFlow Metal
    TensorFlow Metal is an integration that enables TensorFlow to run efficiently on Apple GPUs via the Metal framework, accelerating machine learning workloads on macOS and iOS devices.
  • D. XLA
    XLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes and accelerates machine learning computations on hardware such as TPUs and GPUs.
  • E. 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.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b9be5d0c819097e006f32d98753a completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 10:24 a.m.