Triple

T21170481
Position Surface form Disambiguated ID Type / Status
Subject Sutton Foster E521677 entity
Predicate spouse P13 FINISHED
Object Christian Borle 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: Christian Borle | Statement: [Sutton Foster, spouse, Christian Borle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christian Borle
Context triple: [Sutton Foster, spouse, Christian Borle]
  • A. Christian Borle chosen
    Christian Borle is a Tony Award–winning American stage and screen actor best known for his work in Broadway musicals and television.
  • B. Andrew Rannells
    Andrew Rannells is an American actor and singer best known for his Tony-nominated Broadway work in shows like The Book of Mormon and his roles in television series such as Girls and Black Monday.
  • C. Anthony Warlow
    Anthony Warlow is an acclaimed Australian baritone and musical theatre performer renowned for his leading roles in major stage productions and recordings.
  • D. Jefferson Mays
    Jefferson Mays is a Tony Award–winning American stage and screen actor renowned for his virtuosity in playing multiple roles and his work in both Broadway productions and film/television.
  • E. Dylan Baker
    Dylan Baker is an American character actor known for his versatile roles in film, television, and theater, including appearances in movies like "Planes, Trains and Automobiles" and the "Spider-Man" series.
  • 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_69e0b50e30748190b186824a206d39b9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72712893081908e394ccc7e0cbb53 completed April 21, 2026, 7:28 a.m.
Created at: April 16, 2026, 3 p.m.