Triple

T14388378
Position Surface form Disambiguated ID Type / Status
Subject Tensor SoC family E356780 entity
Predicate marketedAs P1395 FINISHED
Object Google Tensor E72121 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: Google Tensor | Statement: [Tensor SoC family, marketedAs, Google Tensor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Google Tensor
Context triple: [Tensor SoC family, marketedAs, Google Tensor]
  • A. Google Tensor chosen
    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. Google TPU
    Google TPU is a custom-designed application-specific integrated circuit (ASIC) developed by Google to accelerate machine learning workloads, particularly deep learning inference and training in its data centers.
  • C. Google Brain
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • D. Google AI Studio
    Google AI Studio is a web-based development environment from Google that lets developers build, test, and integrate applications using Gemini and other Google AI models.
  • 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.

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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90283b9c8190b50d30ad58bfe085 completed April 14, 2026, 7:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94a254f881908d9494d4602064ae completed May 8, 2026, 7:45 a.m.
Created at: April 10, 2026, 1:16 a.m.