Triple

T2373688
Position Surface form Disambiguated ID Type / Status
Subject Quoc V. Le E46144 entity
Predicate coAuthorWith P398 FINISHED
Object Ilya Sutskever E11116 NE FINISHED

How this triple was built (2 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: Ilya Sutskever | Statement: [Quoc V. Le, coAuthorWith, Ilya Sutskever]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ilya Sutskever
Context triple: [Quoc V. Le, coAuthorWith, Ilya Sutskever]
  • A. Ilya Sutskever chosen
    Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
  • B. Volodymyr Mnih
    Volodymyr Mnih is a computer scientist and deep learning researcher known for pioneering deep reinforcement learning methods that achieved human-level performance on Atari games.
  • C. Alex Krizhevsky
    Alex Krizhevsky is a computer scientist best known for co-developing the AlexNet convolutional neural network, which revolutionized deep learning in computer vision.
  • D. Ian Goodfellow
    Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
  • E. Christian Szegedy
    Christian Szegedy is a computer scientist and AI researcher known for his influential work on deep learning and convolutional neural networks, including contributions to the Inception architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc791c4688190a4b8f0e540e84eb4 completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8a8c2b88190a18dbf35d745958f completed March 9, 2026, 11:02 a.m.
Created at: March 4, 2026, 7:56 p.m.