Triple

T4424749
Position Surface form Disambiguated ID Type / Status
Subject ICLR E95182 entity
Predicate coFounder P2835 FINISHED
Object Aaron Courville E28350 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: Aaron Courville | Statement: [ICLR, coFounder, Aaron Courville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aaron Courville
Context triple: [ICLR, coFounder, Aaron Courville]
  • A. Aaron Courville chosen
    Aaron Courville is a machine learning researcher and professor best known as a co-author of the influential deep learning textbook alongside Yoshua Bengio and Ian Goodfellow.
  • B. Eric Thibault
    Eric Thibault is a professional basketball coach best known for leading the WNBA’s Washington Mystics.
  • C. Alex Courtes
    Alex Courtes is a French director and designer best known for his innovative music videos and visual work with major rock and electronic artists.
  • D. Christian LeBlanc
    Christian LeBlanc is an American actor best known for his long-running role as Michael Baldwin on the soap opera "The Young and the Restless."
  • E. Mark Gastineau
    Mark Gastineau is a former American football defensive end best known as a star pass rusher for the New York Jets in the 1980s and a key member of the famed "New York Sack Exchange" defensive line.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3554ca5208190ba2661616dcf071c completed March 13, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f62f7eb88190a02669845126e790 completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:30 p.m.