Triple

T7055492
Position Surface form Disambiguated ID Type / Status
Subject Mary Holden E164077 entity
Predicate castMemberWith P74774 FINISHED
Object Margaret Early E197328 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: Margaret Early | Statement: [Mary Holden, castMemberWith, Margaret Early]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Early
Context triple: [Mary Holden, castMemberWith, Margaret Early]
  • A. Margaret Early chosen
    Margaret Early was an American film actress active in the late 1930s and 1940s, known for her wholesome screen presence in Hollywood musicals and comedies.
  • B. Margaret Booth
    Margaret Booth was a pioneering American film editor and longtime MGM supervising editor whose career spanned the silent era through Hollywood’s Golden Age.
  • C. Margaret Nichols
    Margaret Nichols was the wife of American film and television producer Hal Roach.
  • D. Margaret Wade
    Margaret Wade was a pioneering American women’s basketball coach, best known for leading Delta State University to multiple national championships in the 1970s and for having the Wade Trophy, women’s basketball’s top collegiate player award, named in her honor.
  • E. Margaret Johnston
    Margaret Johnston was a British actress known for her work on stage and in films during 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_69c68861678881909961ddf4d779f750 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e77415e88190ab65137382f1b155 completed March 27, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7889ddd488190b1e55828909133eb completed March 28, 2026, 7:51 a.m.
Created at: March 27, 2026, 2:38 p.m.