Triple

T15499056
Position Surface form Disambiguated ID Type / Status
Subject Kenneth More E378899 entity
Predicate employer P7 FINISHED
Object Rank Organisation E39732 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: Rank Organisation | Statement: [Kenneth More, employer, Rank Organisation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rank Organisation
Context triple: [Kenneth More, employer, Rank Organisation]
  • A. Rank Organisation chosen
    Rank Organisation was a major British film production, distribution, and exhibition company that played a central role in the UK cinema industry in the mid-20th century.
  • B. Rank
    Rank is a surname most notably associated with J. Arthur Rank, the influential British industrialist and film producer who founded the Rank Organisation.
  • C. The Rank Organisation
    The Rank Organisation was a major British entertainment conglomerate best known for its film production and distribution during the mid-20th century.
  • D. table of ranks
    The table of ranks was an 18th-century Russian system that organized civil and military positions into a formal hierarchy, helping to restructure the state bureaucracy and nobility.
  • E. Order of Merit ranking
    The Order of Merit ranking is a season-long money-based leaderboard used to determine the top-performing players on the Asian Tour.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3667a53c81908be789f99e580265 completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:53 a.m.