Triple

T5791484
Position Surface form Disambiguated ID Type / Status
Subject The Ghost and Mrs. Muir E128403 entity
Predicate characterPortrayed P1507 FINISHED
Object Miles Fairley E557820 NE FINISHED

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: Miles Fairley | Statement: [The Ghost and Mrs. Muir, characterPortrayed, Miles Fairley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miles Fairley
Context triple: [The Ghost and Mrs. Muir, characterPortrayed, Miles Fairley]
  • A. Miles Fairley chosen
    Miles Fairley is a charming but duplicitous children's book author who becomes a romantic interest of the protagonist in the classic film "The Ghost and Mrs. Muir."
  • B. Miles Goodman
    Miles Goodman was an American composer and jazz record producer best known for his film scores, particularly for popular comedies of the 1980s and early 1990s.
  • C. Walker Edmiston
    Walker Edmiston was an American character actor and voice artist known for his extensive work in television, film, and animation from the 1950s through the 1990s.
  • D. Jack Mullaney
    Jack Mullaney was an American character actor known for his comedic roles in mid-20th-century film and television.
  • E. Felix Mills
    Felix Mills was an American composer and arranger best known for his work on film scores and radio programs in the mid-20th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a56c73c81908a1c72c86e474b54 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107e64edc819080b3ebf9b9137749 completed March 23, 2026, 9:29 a.m.
Created at: March 22, 2026, 3:51 p.m.