Triple

T4654878
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow Extended E102383 entity
Predicate usesLibrary P4791 FINISHED
Object TensorFlow Serving
TensorFlow Serving is a flexible, high-performance system for deploying and serving machine learning models in production, particularly those built with TensorFlow.
 E457353 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 Serving | Statement: [TensorFlow Extended, usesLibrary, TensorFlow Serving]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Serving
Context triple: [TensorFlow Extended, usesLibrary, TensorFlow Serving]
  • 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 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. 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.
  • E. 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.
  • 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 Serving
Triple: [TensorFlow Extended, usesLibrary, TensorFlow Serving]
Generated description
TensorFlow Serving is a flexible, high-performance system for deploying and serving machine learning models in production, particularly those built with TensorFlow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TensorFlow Serving
Target entity description: TensorFlow Serving is a flexible, high-performance system for deploying and serving machine learning models in production, particularly those built with TensorFlow.
  • 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 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. 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.
  • E. 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.
  • 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.