Triple

T22412031
Position Surface form Disambiguated ID Type / Status
Subject DNNresearch Inc. E554014 entity
Predicate notableEmployee P304 FINISHED
Object Geoffrey Hinton NE NERFINISHED

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: Geoffrey Hinton | Statement: [DNNresearch Inc., notableEmployee, Geoffrey Hinton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geoffrey Hinton
Context triple: [DNNresearch Inc., notableEmployee, Geoffrey Hinton]
  • A. Geoffrey Hinton chosen
    Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and 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. 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.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4e6ce8819085a1e06d886bf21c completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15943dd84819099e77563da470594 completed April 29, 2026, 1:05 a.m.
Created at: April 16, 2026, 8:46 p.m.