Triple

T21766916
Position Surface form Disambiguated ID Type / Status
Subject Thousands Cheer E537316 entity
Predicate castMember P1668 FINISHED
Object Virginia O'Brien 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: Virginia O'Brien | Statement: [Thousands Cheer, castMember, Virginia O'Brien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Virginia O'Brien
Context triple: [Thousands Cheer, castMember, Virginia O'Brien]
  • A. Virginia O'Brien chosen
    Virginia O'Brien was an American film actress and singer best known for her deadpan comedic style and musical performances in MGM musicals of the 1940s.
  • B. Grace O'Brien
    Grace O'Brien is a character in the television series "Doctor Who," known as the wise and compassionate grandmother of companion Ryan Sinclair.
  • C. Florence Dempsey
    Florence Dempsey is a spirited young reporter character in the 1933 horror film "Mystery of the Wax Museum," known for her sharp wit and investigative tenacity.
  • D. Karen O’Brien
    Karen O’Brien is a British academic and university leader who serves as Vice-Chancellor of Durham University, overseeing its strategic direction and academic mission.
  • E. Virginia O'Connor
    Virginia O'Connor was the wife of renowned American composer and conductor Henry Mancini.
  • 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_69e0c46f5d1c8190bf830409e98464e5 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f031aa9c888190887c5c1d1e3bab9f completed April 28, 2026, 4:03 a.m.
Created at: April 16, 2026, 6:51 p.m.