Triple

T6305592
Position Surface form Disambiguated ID Type / Status
Subject Freddie Young E141366 entity
Predicate employer P7 FINISHED
Object London Films E191031 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: London Films | Statement: [Freddie Young, employer, London Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London Films
Context triple: [Freddie Young, employer, London Films]
  • A. London Films chosen
    London Films is a British film production company best known for its classic mid-20th-century films produced under the leadership of Alexander Korda.
  • B. Film London
    Film London is the capital’s screen industries agency, responsible for promoting and developing film, television, and media production in London.
  • C. London Film Festival
    The London Film Festival is a major annual film festival held in London, showcasing a wide range of international cinema and hosting high-profile premieres.
  • D. Clerkenwell Films
    Clerkenwell Films is a British television and film production company known for creating acclaimed dramas and comedies such as "Misfits" and "Lovesick."
  • E. BBC Films
    BBC Films is the feature film-making arm of the BBC, known for producing and co-producing a wide range of acclaimed British and international movies.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06479acec819090306a155a03b774 completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e44527488190b3d605e917c8dfb2 completed March 27, 2026, 1:58 a.m.
Created at: March 22, 2026, 4:28 p.m.