Triple

T17598476
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow ecosystem E428633 entity
Predicate includesComponent P1393 FINISHED
Object TensorFlow Graphics — NE NERFINISHED

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: TensorFlow Graphics | Statement: [TensorFlow ecosystem, includesComponent, TensorFlow Graphics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Graphics
Context triple: [TensorFlow ecosystem, includesComponent, TensorFlow Graphics]
  • A. TensorFlow Extended
    TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
  • B. 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.
  • C. TensorFlow ecosystem
    The TensorFlow ecosystem is a comprehensive suite of tools, libraries, and extensions built around the TensorFlow machine learning framework to support model development, training, deployment, and visualization.
  • D. TensorFlow.js
    TensorFlow.js is a JavaScript library that enables training and running machine learning models directly in the browser and in Node.js using TensorFlow.
  • E. Swift for TensorFlow
    Swift for TensorFlow is an experimental machine learning platform that integrates TensorFlow directly into the Swift programming language to enable differentiable programming and high-performance model development.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Graphics
Target entity description: TensorFlow Graphics is a library built on TensorFlow that provides differentiable rendering and 3D computer vision tools for deep learning workflows involving geometric data.
  • A. TensorFlow Extended
    TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
  • B. 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.
  • C. TensorFlow ecosystem
    The TensorFlow ecosystem is a comprehensive suite of tools, libraries, and extensions built around the TensorFlow machine learning framework to support model development, training, deployment, and visualization.
  • D. TensorFlow.js
    TensorFlow.js is a JavaScript library that enables training and running machine learning models directly in the browser and in Node.js using TensorFlow.
  • E. Swift for TensorFlow
    Swift for TensorFlow is an experimental machine learning platform that integrates TensorFlow directly into the Swift programming language to enable differentiable programming and high-performance model development.
  • F. None of above. chosen

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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c474e5481909d2736241b592dab completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.