Triple

T5590956
Position Surface form Disambiguated ID Type / Status
Subject The Thin Man E146874 entity
Predicate castMember P1668 FINISHED
Object Harold Huber E459986 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: Harold Huber | Statement: [The Thin Man, castMember, Harold Huber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harold Huber
Context triple: [The Thin Man, castMember, Harold Huber]
  • A. Harold Huber chosen
    Harold Huber was an American character actor known for his prolific work in 1930s and 1940s Hollywood films, often portraying suave or villainous supporting roles.
  • B. Harold Huth
    Harold Huth was a British film director, producer, and occasional actor active in the mid-20th century, known for his work in the British studio system.
  • C. Harold Schmidt
    Harold Schmidt is a relatively obscure individual whose name is shared with several people, including professionals in fields such as sports, academia, and the arts.
  • D. Walt Dohrn
    Walt Dohrn is an American animator, voice actor, writer, and director best known for his creative leadership on DreamWorks Animation films such as the Trolls franchise.
  • E. George Boemler
    George Boemler was a film editor known for his work on classic Hollywood productions, including the musical comedy "High Society."
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020a1d4cc8190a52264dfba6aa011 completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107b36b3c819084d7e8fda4de74b7 completed March 23, 2026, 9:28 a.m.
Created at: March 22, 2026, 3:38 p.m.