Triple

T17837342
Position Surface form Disambiguated ID Type / Status
Subject Richard Arlen E445424 entity
Predicate name P16 FINISHED
Object Richard Arlen 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: Richard Arlen | Statement: [Richard Arlen, name, Richard Arlen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Arlen
Context triple: [Richard Arlen, name, Richard Arlen]
  • A. Richard Arlen chosen
    Richard Arlen was an American film actor best known for his roles in early Hollywood, particularly in silent and early sound-era adventure and war films.
  • B. Barry Livesey
    Barry Livesey was a British actor active in the early to mid-20th century, known for his work on stage and in film and as a member of the prominent Livesey acting family.
  • C. Louis Hayward
    Louis Hayward was a British-born American film and television actor known for his suave, debonair roles in adventure films and dramas from the 1930s through the 1950s.
  • D. George Brent
    George Brent was an Irish-American leading man of 1930s and 1940s Hollywood cinema, known for his suave screen presence opposite stars like Bette Davis.
  • E. Jack Cardiff
    Jack Cardiff was an acclaimed British cinematographer and director renowned for his pioneering use of Technicolor and visually striking work on classic films.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d28c14881909033abd09bbdb135 completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:16 a.m.