Triple

T9163364
Position Surface form Disambiguated ID Type / Status
Subject Conrad Jarrett E219884 entity
Predicate creator P184 FINISHED
Object Judith Guest E708729 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: Judith Guest | Statement: [Conrad Jarrett, creator, Judith Guest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Judith Guest
Context triple: [Conrad Jarrett, creator, Judith Guest]
  • A. Judith Guest chosen
    Judith Guest is an American novelist best known for her debut novel "Ordinary People," which was adapted into an Academy Award–winning film.
  • B. Lee Smith
    Lee Smith is a Hall of Fame former Major League Baseball closer renowned as one of the most dominant relief pitchers of his era.
  • C. Lee Smith
    Lee Smith is an acclaimed Australian film editor known for his work on major films such as Christopher Nolan’s The Dark Knight trilogy and Dunkirk.
  • D. Paulette Jiles
    Paulette Jiles is an American poet and novelist best known for her historical fiction, including the novel "News of the World."
  • E. 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."
  • 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_69ca83e3633c81908688a9fa2306ba99 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaa2d6628819084ac4734650fe912 completed April 1, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0547df750819095853f21cf740c63 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:21 p.m.