Triple

T15385653
Position Surface form Disambiguated ID Type / Status
Subject Red, White and Blue E367909 entity
Predicate productionCompany P490 FINISHED
Object BBC Films E115202 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: BBC Films | Statement: [Red, White and Blue, productionCompany, BBC Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BBC Films
Context triple: [Red, White and Blue, productionCompany, BBC Films]
  • A. BBC Films chosen
    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.
  • B. BBC Productions
    BBC Productions is a television production arm of the British Broadcasting Corporation responsible for creating a wide range of factual and entertainment programming.
  • C. British Screen Productions
    British Screen Productions was a UK-based film production company known for supporting distinctive and often unconventional British and international cinema.
  • D. Shaftesbury Films
    Shaftesbury Films is a Canadian television and film production company known for creating popular series such as Murdoch Mysteries.
  • E. Arrow Films
    Arrow Films is a British home video and film distribution company known for releasing cult, classic, and genre cinema in high-quality restored editions.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e74ff70819094c1a85f51d6e228 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1349bad48190a31c50a0c5104128 completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:19 a.m.