Triple

T23216462
Position Surface form Disambiguated ID Type / Status
Subject Judy Maxwell E580757 entity
Predicate romanticInterestOf P7325 FINISHED
Object Howard Bannister 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: Howard Bannister | Statement: [Judy Maxwell, romanticInterestOf, Howard Bannister]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Bannister
Context triple: [Judy Maxwell, romanticInterestOf, Howard Bannister]
  • A. Howard Bannister chosen
    Howard Bannister is the mild-mannered, musicologist protagonist played by Ryan O'Neal in the screwball comedy film "What's Up, Doc?".
  • B. Michael Bannister
    Michael Bannister is a musician best known as a member of the Scottish indie rock supergroup Reindeer Section.
  • C. Henry Buckley
    Henry Buckley is a personal name shared by several notable individuals, including politicians, journalists, and public figures.
  • D. Scott Banister
    Scott Banister is an American entrepreneur and angel investor known for co-founding IronPort and early involvement with companies like PayPal and Facebook.
  • E. Frank Worthington
    Frank Worthington was an English professional footballer best known as a flamboyant forward who played for clubs such as Leicester City and Bolton Wanderers during the 1970s and 1980s.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f19165949c81908e4d66a8a2b0a25a completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.