Triple

T17880478
Position Surface form Disambiguated ID Type / Status
Subject Stevie E447069 entity
Predicate castMember P1668 FINISHED
Object Mona Washbourne 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: Mona Washbourne | Statement: [Stevie, castMember, Mona Washbourne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona Washbourne
Context triple: [Stevie, castMember, Mona Washbourne]
  • A. Mona Washbourne chosen
    Mona Washbourne was an English character actress known for her versatile performances in mid-20th-century British film, television, and theatre.
  • B. Mona Sutphen
    Mona Sutphen is an American foreign policy expert and former White House official who served in senior national security and diplomatic roles under President Barack Obama.
  • C. Mona Kane
    Mona Kane is a long-running supporting character on the soap opera "All My Children," best known as the kind, moral, and often-suffering mother of central heroine Erica Kane.
  • D. Georgia Welch
    Georgia Welch is best known as the wife of former U.S. Attorney General and prominent civil rights advocate Ramsey Clark.
  • E. Mona Lee Fultz
    Mona Lee Fultz is an American actress known for her work in film, television, and theater, including a role in the cult mockumentary film "True Stories."
  • 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49c0e56bc819097649377b520de63 completed April 19, 2026, 9:10 a.m.
Created at: April 10, 2026, 10:18 a.m.