Triple

T4035545
Position Surface form Disambiguated ID Type / Status
Subject Behind a Mask E83818 entity
Predicate mainCharacter P1183 FINISHED
Object Jean Muir E213624 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: Jean Muir | Statement: [Behind a Mask, mainCharacter, Jean Muir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Muir
Context triple: [Behind a Mask, mainCharacter, Jean Muir]
  • A. Jean Muir chosen
    Jean Muir was an American film, stage, and television actress active in the 1930s and 1940s, known for her roles in Hollywood productions and later for being one of the first performers blacklisted during the Red Scare.
  • B. Mary Mackilwean
    Mary Mackilwean was the wife of Richard Caswell, the first governor of the U.S. state of North Carolina.
  • C. Laura Gardin Fraser
    Laura Gardin Fraser was a prominent American sculptor and medalist known for her commemorative coins and public monuments in the early 20th century.
  • D. Janet Munro
    Janet Munro was a British actress best known for her roles in several late-1950s and early-1960s Disney films.
  • E. Mary Campbell
    Mary Campbell is a central character in the satirical television sitcom "Soap," known for her role in the show's parody of daytime soap opera tropes.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb132f6c8190937acd35a6a5a9e4 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5629748d88190984cce08eef05e9c completed March 14, 2026, 1:28 p.m.
Created at: March 9, 2026, 3:36 p.m.