Triple

T560503
Position Surface form Disambiguated ID Type / Status
Subject Deep Learning (book) E13438 entity
Predicate author P4 FINISHED
Object Yoshua Bengio E1098 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: Yoshua Bengio | Statement: [Deep Learning (book), author, Yoshua Bengio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yoshua Bengio
Context triple: [Deep Learning (book), author, Yoshua Bengio]
  • A. Yoshua Bengio chosen
    Yoshua Bengio is a Canadian computer scientist and deep learning pioneer whose work on neural networks and representation learning has been foundational to modern artificial intelligence.
  • B. Samy Bengio
    Samy Bengio is a prominent machine learning researcher known for his contributions to deep learning and his leadership roles at major AI organizations including Google and Apple.
  • C. Yann LeCun
    Yann LeCun is a pioneering computer scientist best known for his foundational work in deep learning and convolutional neural networks, which has profoundly shaped modern artificial intelligence.
  • D. Geoffrey Hinton
    Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
  • E. 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."
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499e13694819087a236bffa6601a9 completed March 1, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4fc7dea048190a5a1472825f6d747 completed March 2, 2026, 2:57 a.m.
Created at: March 1, 2026, 7:32 p.m.