Triple

T16685234
Position Surface form Disambiguated ID Type / Status
Subject Herbert Wise E405445 entity
Predicate name P16 FINISHED
Object Herbert Wise E405445 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: Herbert Wise | Statement: [Herbert Wise, name, Herbert Wise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herbert Wise
Context triple: [Herbert Wise, name, Herbert Wise]
  • A. Herbert Wise chosen
    Herbert Wise was a British television and film director best known for his acclaimed work on period dramas and literary adaptations.
  • B. Herbert Woods
    Herbert Woods is best known as the husband of renowned American harpist and businesswoman Sylvia Woods.
  • C. Herbert Horne
    Herbert Horne was a British designer, typographer, art historian, and key figure in the Arts and Crafts movement who helped shape late 19th-century artistic and craft reform in England.
  • D. Herbert Clarke
    Herbert Clarke was a British ice hockey player who competed at the 1924 Winter Olympics in Chamonix, France.
  • E. Herbert Fisher
    Herbert Fisher was a British historian and Liberal politician who served as President of the Board of Education in the early 20th century.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea550c0819085bd36c44237a61a completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b27dcef481909ccfe4d3d604b1de completed May 10, 2026, 4:29 p.m.
Created at: April 10, 2026, 5:19 a.m.