Triple

T143829
Position Surface form Disambiguated ID Type / Status
Subject Yann LeCun E2909 entity
Predicate fullName P16 FINISHED
Object Yann André LeCun E2909 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: Yann André LeCun | Statement: [Yann LeCun, fullName, Yann André LeCun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yann André LeCun
Context triple: [Yann LeCun, fullName, Yann André LeCun]
  • A. Yann LeCun chosen
    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.
  • B. Yoshua Bengio
    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.
  • C. Geoffrey Hinton
    Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
  • 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. Ilya Sutskever
    Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
  • 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_69a2521e35c08190b28e5c9f1e3c9b59 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a257caf678819092e975d5167f9df4 completed Feb. 28, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2bf691a848190a4f6e40d9aea2168 completed Feb. 28, 2026, 10:11 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.