Triple

T22133344
Position Surface form Disambiguated ID Type / Status
Subject Over the Moon E546961 entity
Predicate voiceActor P1507 FINISHED
Object Ruthie Ann Miles 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: Ruthie Ann Miles | Statement: [Over the Moon, voiceActor, Ruthie Ann Miles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruthie Ann Miles
Context triple: [Over the Moon, voiceActor, Ruthie Ann Miles]
  • A. Ruthie Ann Miles chosen
    Ruthie Ann Miles is a Tony Award–winning American actress and singer known for her work in musical theatre, television, and film.
  • B. Daphne Rubin-Vega
    Daphne Rubin-Vega is a Panamanian-American actress and singer best known for originating the role of Mimi Márquez in the groundbreaking Broadway musical Rent.
  • C. Shoshana Bean
    Shoshana Bean is an American singer and Broadway performer known for her powerful vocals and roles in shows like Wicked and Waitress.
  • D. Sylvia Miles
    Sylvia Miles was an American actress best known for her Oscar-nominated supporting role as a jaded New York socialite in the film "Midnight Cowboy."
  • E. Laura Benét
    Laura Benét was an American writer and poet known for her biographies and historical works for young readers, and as a member of the literary Benét family.
  • 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_69e11e39bf348190b541bfa16a7b71e0 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129b81d5c819085fd18bf3ae28333 completed April 28, 2026, 9:42 p.m.
Created at: April 16, 2026, 8:32 p.m.