Triple

T4654877
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow Extended E102383 entity
Predicate usesLibrary P4791 FINISHED
Object TensorFlow Model Analysis
TensorFlow Model Analysis is an open-source library for evaluating, validating, and monitoring machine learning models—especially at scale and on large datasets—within TensorFlow-based pipelines.
 E457352 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 Model Analysis | Statement: [TensorFlow Extended, usesLibrary, TensorFlow Model Analysis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Model Analysis
Context triple: [TensorFlow Extended, usesLibrary, TensorFlow Model Analysis]
  • 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 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.
  • C. TensorFlow Estimators
    TensorFlow Estimators are a high-level TensorFlow API that simplifies building, training, and deploying machine learning models with standardized workflows and production-ready features.
  • D. 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.
  • 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. 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 Model Analysis
Triple: [TensorFlow Extended, usesLibrary, TensorFlow Model Analysis]
Generated description
TensorFlow Model Analysis is an open-source library for evaluating, validating, and monitoring machine learning models—especially at scale and on large datasets—within TensorFlow-based pipelines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Model Analysis
Target entity description: TensorFlow Model Analysis is an open-source library for evaluating, validating, and monitoring machine learning models—especially at scale and on large datasets—within TensorFlow-based pipelines.
  • 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 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.
  • C. TensorFlow Estimators
    TensorFlow Estimators are a high-level TensorFlow API that simplifies building, training, and deploying machine learning models with standardized workflows and production-ready features.
  • D. 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.
  • 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. 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6317ba70819089145766d3462e57 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaef125c819097d79f25608302dc completed March 21, 2026, 1:57 a.m.
NEDg Description generation batch_69bdfc0964c881909e6b98a1c8ea747f completed March 21, 2026, 2:01 a.m.
NED2 Entity disambiguation (via description) batch_69bdfce1be788190ae3418df301e5136 completed March 21, 2026, 2:05 a.m.
Created at: March 20, 2026, 1:14 p.m.