Triple

T12288976
Position Surface form Disambiguated ID Type / Status
Subject Jesse James (1939 film) E292903 entity
Predicate castMember P1668 FINISHED
Object Ernest Whitman E600501 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: Ernest Whitman | Statement: [Jesse James (1939 film), castMember, Ernest Whitman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernest Whitman
Context triple: [Jesse James (1939 film), castMember, Ernest Whitman]
  • A. Ernest Whitman chosen
    Ernest Whitman was an American character actor known for his supporting roles in films and on radio during the 1930s and 1940s.
  • B. George Whitman
    George Whitman was an American-born bookseller and literary figure best known for running and transforming Paris’s iconic Shakespeare and Company bookshop into a haven for writers and readers.
  • C. Ernest Miller
    Ernest Miller was an American cinematographer known for his work on numerous Western films and serials during the early to mid-20th century.
  • D. Edwin Blashfield
    Edwin Blashfield was an American muralist and painter best known for his large-scale allegorical works in prominent public buildings across the United States.
  • E. Frank Seiberling
    Frank Seiberling was an American industrialist best known for founding the Goodyear Tire & Rubber Company, which became one of the world’s leading tire manufacturers.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91d21692481908c97edc3d602f1d5 completed April 10, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e752f3c8190ba0e273f3e41a321 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:52 p.m.