Triple

T8849385
Position Surface form Disambiguated ID Type / Status
Subject Pierre Sermanet E210596 entity
Predicate coAuthorWith P398 FINISHED
Object Rob Fergus E470958 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: Rob Fergus | Statement: [Pierre Sermanet, coAuthorWith, Rob Fergus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rob Fergus
Context triple: [Pierre Sermanet, coAuthorWith, Rob Fergus]
  • A. Rob Fergus chosen
    Rob Fergus is a computer scientist and researcher in machine learning and computer vision, known for his influential work in deep learning and academic leadership in AI.
  • B. Kevin Fagan
    Kevin Fagan is the American cartoonist best known as the creator of the long-running comic strip "Drabble."
  • C. Dan Fagan
    Dan Fagan is a notable individual recognized for achievements associated with the surname Fagan.
  • D. Mitch Rouse
    Mitch Rouse is an American actor, comedian, and writer known for his work in film and television, including co-creating the series "Strangers with Candy" and appearing in numerous comedic roles.
  • E. Greg Finton
    Greg Finton is a film editor known for his work on documentaries and feature films, including the acclaimed documentary "He Named Me Malala."
  • 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_69ca838a424c8190b1ecac115c2927e7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60abb0748190af41d4e1f419e39c completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0171e98a081909875c96defaf9bfa completed April 3, 2026, 7:38 p.m.
Created at: March 30, 2026, 6:49 p.m.