Triple

T19619461
Position Surface form Disambiguated ID Type / Status
Subject Rob Fergus E470958 entity
Predicate coauthor P2389 FINISHED
Object Ian Goodfellow 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: Ian Goodfellow | Statement: [Rob Fergus, coauthor, Ian Goodfellow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ian Goodfellow
Context triple: [Rob Fergus, coauthor, Ian Goodfellow]
  • A. Ian Goodfellow chosen
    Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
  • B. Ilya Goodfellow
    Ilya Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and contributing to deep learning at organizations like Google and OpenAI.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640e4570c81909fc4f9b871346337 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:43 p.m.