Triple

T20774632
Position Surface form Disambiguated ID Type / Status
Subject Elise Clifton-Ward E511322 entity
Predicate meets P1220 FINISHED
Object Frank Tupelo 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: Frank Tupelo | Statement: [Elise Clifton-Ward, meets, Frank Tupelo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank Tupelo
Context triple: [Elise Clifton-Ward, meets, Frank Tupelo]
  • A. Frank Tupelo chosen
    Frank Tupelo is the seemingly ordinary American math teacher who becomes entangled in an international web of intrigue and mistaken identity in the film "The Tourist."
  • B. John Esten Cooke
    John Esten Cooke was a 19th-century American novelist and Confederate soldier best known for his historical romances set in Virginia and his writings about the American Civil War.
  • C. Hal Lanier
    Hal Lanier is a former Major League Baseball infielder and manager best known for leading the Houston Astros to success in the mid-1980s.
  • D. Nelson Tift
    Nelson Tift was a 19th-century American lawyer, politician, and entrepreneur best known as the founder and early developer of Albany, Georgia.
  • E. Clarence Upson Young
    Clarence Upson Young was an American screenwriter active during Hollywood’s classic era, known for contributing to genre films including mystery and horror.
  • 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_69e0b4cac7a48190a715cb3d545df2b4 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c26a39bc81909ca5d102056d8586 completed April 21, 2026, 12:18 a.m.
Created at: April 16, 2026, 12:37 p.m.