Triple

T10918381
Position Surface form Disambiguated ID Type / Status
Subject Altitude Film Distribution E257883 entity
Predicate foundedBy P104 FINISHED
Object Will Clarke E883702 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: Will Clarke | Statement: [Altitude Film Distribution, foundedBy, Will Clarke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Will Clarke
Context triple: [Altitude Film Distribution, foundedBy, Will Clarke]
  • A. Will Clarke chosen
    Will Clarke is a film producer best known for his work on the British romantic comedy "Chalet Girl."
  • B. Brian Clarke
    Brian Clarke is a British artist and leading contemporary stained glass designer known for his innovative architectural glass works and collaborations with prominent cultural figures.
  • C. John Sleeper Clarke
    John Sleeper Clarke was a 19th-century American comic actor and theater manager, known for his successful stage career in both the United States and England.
  • D. Andrew Clark
    Andrew Clark is a relatively common personal name shared by multiple individuals across various professions, including sports, academia, and the arts.
  • E. Ed Clarke
    Ed Clarke is a sound designer known for his work on major theatre productions, including the National Theatre staging of "Frankenstein."
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77080317881909fc50ac3576cefa8 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2170bb97c81908e8d209ddb630601 completed April 17, 2026, 11:18 a.m.
Created at: April 8, 2026, 9:22 p.m.