Triple

T507305
Position Surface form Disambiguated ID Type / Status
Subject Phillips Exeter Academy E10527 entity
Predicate hasAlumni P51 FINISHED
Object John Irving E44109 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: John Irving | Statement: [Phillips Exeter Academy, hasAlumni, John Irving]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Irving
Context triple: [Phillips Exeter Academy, hasAlumni, John Irving]
  • A. John Irving chosen
    John Irving is an American novelist and screenwriter best known for works such as "The World According to Garp," "The Cider House Rules," and "A Prayer for Owen Meany," which often blend dark humor with complex family dramas.
  • B. Richard Yates
    Richard Yates was an American politician who served as the Civil War–era governor of Illinois and later as a U.S. senator.
  • C. Jack Kinney
    Jack Kinney was an American animator and director best known for his work on classic Disney cartoons and feature segments during the mid-20th century.
  • D. Fannie Flagg
    Fannie Flagg is an American author, actress, and comedian best known for her novel "Fried Green Tomatoes at the Whistle Stop Cafe," which was adapted into the popular film "Fried Green Tomatoes."
  • E. Alan Webber
    Alan Webber is an American politician and former business magazine co-founder who serves as the mayor of Santa Fe, New Mexico.
  • 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_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f14dcd688190ad47a3b31b95b6d4 completed Feb. 28, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a498506418819090190a35e8763982 completed March 1, 2026, 7:49 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.