Triple

T12522575
Position Surface form Disambiguated ID Type / Status
Subject Old Man Rhythm E299354 entity
Predicate starring P1507 FINISHED
Object George Barbier E694558 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: George Barbier | Statement: [Old Man Rhythm, starring, George Barbier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Barbier
Context triple: [Old Man Rhythm, starring, George Barbier]
  • A. George Barbier chosen
    George Barbier was an American character actor of the early 20th century, known for his numerous supporting roles in Hollywood films and on Broadway.
  • B. Louis Henry Jourdan
    Louis Henry Jourdan is the son of French actor Louis Jourdan, known for his work in classic Hollywood and European cinema.
  • C. Joseph Corré
    Joseph Corré is a British activist and entrepreneur best known as the co-founder of the lingerie brand Agent Provocateur and for his high-profile protests against government surveillance and climate inaction.
  • D. Georges Benoît
    Georges Benoît was a French cinematographer active in early 20th-century cinema, known for his work on both European and American films.
  • E. Louis Seigner
    Louis Seigner was a prominent French actor and long-time member of the Comédie-Française, known for his extensive work in theatre and film.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545c2aa081908e8a5a94d30e23eb completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bc159c88190835fea5c0d9ee799 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.