Triple

T148133
Position Surface form Disambiguated ID Type / Status
Subject Python E3372 entity
Predicate machineLearningLibrary P7265 FINISHED
Object 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.
E17662 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 | Statement: [Python, machineLearningLibrary, TensorFlow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TensorFlow
Context triple: [Python, machineLearningLibrary, TensorFlow]
  • A. Google Brain
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • B. DeepMind
    DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
  • C. LeNet
    LeNet is one of the earliest convolutional neural network architectures, pioneering modern deep learning approaches to image recognition and handwritten digit classification.
  • D. Deep Learning (book)
    Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
  • E. Vector Institute for Artificial Intelligence
    The Vector Institute for Artificial Intelligence is a Toronto-based research institute focused on advancing cutting-edge AI and machine learning, known for its association with leading researchers such as Geoffrey Hinton.
  • 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
Triple: [Python, machineLearningLibrary, TensorFlow]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TensorFlow
Target entity description: 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.
  • A. Google Brain
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • B. DeepMind
    DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
  • C. LeNet
    LeNet is one of the earliest convolutional neural network architectures, pioneering modern deep learning approaches to image recognition and handwritten digit classification.
  • D. Deep Learning (book)
    Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
  • E. Vector Institute for Artificial Intelligence
    The Vector Institute for Artificial Intelligence is a Toronto-based research institute focused on advancing cutting-edge AI and machine learning, known for its association with leading researchers such as Geoffrey Hinton.
  • 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a25bab43608190ba5ebfbee6b5b6e4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2c27754a881908ef5a96e05e515e3 completed Feb. 28, 2026, 10:24 a.m.
NEDg Description generation batch_69a2c37177348190857d52872e6ab393 completed Feb. 28, 2026, 10:29 a.m.
NED2 Entity disambiguation (via description) batch_69a2c3c512f08190bb87f874524b1616 completed Feb. 28, 2026, 10:30 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.