Triple

T364253
Position Surface form Disambiguated ID Type / Status
Subject Google Brain E7923 entity
Predicate productDeveloped P490 FINISHED
Object TensorFlow E17662 NE FINISHED

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 | Statement: [Google Brain, productDeveloped, TensorFlow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TensorFlow
Context triple: [Google Brain, productDeveloped, TensorFlow]
  • A. TensorFlow chosen
    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. Keras
    Keras is a high-level neural networks API written in Python that simplifies building, training, and deploying deep learning models, often running on top of frameworks like TensorFlow.
  • C. PyTorch
    PyTorch is an open-source deep learning framework widely used for building and training neural networks, known for its dynamic computation graph and strong support for research and production in Python.
  • D. Google Brain
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: productDeveloped
Context triple: [Google Brain, productDeveloped, TensorFlow]
  • A. produces chosen
    Indicates that one entity creates, generates, or yields another entity as a result or output.
  • B. hasProduct
    Indicates that an entity possesses, offers, or is associated with a particular product.
  • C. developedAs
    Indicates that one entity was created, designed, or evolved specifically to function as or replace another entity.
  • D. developsTechnologyFor
    Indicates that one entity creates, improves, or engineers technology specifically intended to be used by or to benefit another entity.
  • E. inspiredDevelopmentOf
    Indicates that one entity served as a motivating influence or creative stimulus leading to the development or creation of another entity.
  • F. None of above.

Provenance (4 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebd1016481909b8ba3b047a47145 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e86533a481909bab5f0b52114c6a completed March 1, 2026, 7:19 a.m.
PD Predicate disambiguation batch_69a2e95dbb208190b277fc5352a4ee84 completed Feb. 28, 2026, 1:10 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.