Triple

T23538119
Position Surface form Disambiguated ID Type / Status
Subject Mr. Page E577660 entity
Predicate hasName P744 FINISHED
Object Mr. Page 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: Mr. Page | Statement: [Mr. Page, hasName, Mr. Page]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Page
Context triple: [Mr. Page, hasName, Mr. Page]
  • A. Mr. Page chosen
    Mr. Page is a fictional character appearing in the television series "Kristin."
  • B. Peter Page
    Peter Page is one of the central members of the reunited friend group in the British sci-fi comedy film "The World's End," known for his anxious, reserved demeanor amid the chaos of an alien invasion.
  • C. Harry Moseby
    Harry Moseby is a weary, morally conflicted private detective whose search for a missing girl in the 1975 neo-noir film "Night Moves" leads him into a web of betrayal and personal disillusionment.
  • D. Sylvester Potts
    Sylvester Potts was an American singer best known as a key member of the Motown vocal group The Contours.
  • E. Mr. Hall
    Mr. Hall is a character in the stage musical "Clueless," portrayed as a well-meaning but strict high school teacher who becomes the target of a matchmaking scheme.
  • 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1831688190ac06b84729bce160 completed April 29, 2026, 7:07 a.m.
Created at: April 17, 2026, 6:10 p.m.