Triple

T839691
Position Surface form Disambiguated ID Type / Status
Subject Pixel 8 Pro E18148 entity
Predicate neuralProcessingUnit P11229 FINISHED
Object Tensor G3 TPU E97074 NE FINISHED

How this triple was built (3 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: Tensor G3 TPU | Statement: [Pixel 8 Pro, neuralProcessingUnit, Tensor G3 TPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tensor G3 TPU
Context triple: [Pixel 8 Pro, neuralProcessingUnit, Tensor G3 TPU]
  • A. Google Tensor
    Google Tensor is Google's custom-designed system-on-a-chip (SoC) platform created to power Pixel devices with advanced AI and machine learning capabilities.
  • B. TPUs (via XLA integrations)
    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 Extended
    TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
  • D. TPU chosen
    A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
  • E. TensorFlow
    TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: neuralProcessingUnit
Context triple: [Pixel 8 Pro, neuralProcessingUnit, Tensor G3 TPU]
  • A. neuralEngineType chosen
    Indicates the specific kind or category of neural processing engine associated with or used by an entity.
  • B. neuralEnginePerformance
    Indicates the level or efficiency of processing capability provided by a neural engine in performing AI or machine-learning tasks.
  • C. integratesNeuralEngine
    Indicates that one entity incorporates or embeds a neural processing engine within its overall system or architecture.
  • D. cpu
    Indicates that an entity functions as, contains, or is associated with a central processing unit (CPU) in a computational system.
  • E. controlUnitType
    Indicates the specific kind or category of control unit associated with or assigned to an entity.
  • F. None of above.

Provenance (4 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abe4ab1081909207ae2eec1898d9 completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c0144a70819098aa4872a02b62b7 completed March 4, 2026, 5:16 a.m.
PD Predicate disambiguation batch_69a4aa7dfc5c8190890c9df485d73a86 completed March 1, 2026, 9:07 p.m.
Created at: March 1, 2026, 7:38 p.m.