Triple

T816546
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow E17662 entity
Predicate hasComponent P35 FINISHED
Object TensorFlow Extended
TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
 E102383 NE FINISHED

How this triple was built (4 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 Extended | Statement: [TensorFlow, hasComponent, TensorFlow Extended]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Extended
Context triple: [TensorFlow, hasComponent, TensorFlow Extended]
  • A. 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.
  • B. 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.
  • C. TensorFlow Hub
    TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
  • D. 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.
  • E. TensorBoard
    TensorBoard is a visualization and debugging toolkit for TensorFlow that lets users inspect model graphs, track metrics, and analyze training runs.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TensorFlow Extended
Triple: [TensorFlow, hasComponent, TensorFlow Extended]
Generated description
TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Extended
Target entity description: TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
  • A. 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.
  • B. 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.
  • C. TensorFlow Hub
    TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
  • D. 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.
  • E. TensorBoard
    TensorBoard is a visualization and debugging toolkit for TensorFlow that lets users inspect model graphs, track metrics, and analyze training runs.
  • F. None of above. chosen

Provenance (5 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3b47ba481908a8db2bec414a3e4 completed March 4, 2026, 3:15 a.m.
NEDg Description generation batch_69a7a563fa3c81908078cb9b07e28695 completed March 4, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69a7a5c2a95c8190b0d0a385ef035880 completed March 4, 2026, 3:23 a.m.
Created at: March 1, 2026, 7:38 p.m.