Triple

T10140208
Position Surface form Disambiguated ID Type / Status
Subject Ron Saunders E226961 entity
Predicate fullName P16 FINISHED
Object Ronald Saunders E226961 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: Ronald Saunders | Statement: [Ron Saunders, fullName, Ronald Saunders]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ronald Saunders
Context triple: [Ron Saunders, fullName, Ronald Saunders]
  • A. Ronald Adam
    Ronald Adam was a British actor and Royal Air Force officer known for his character roles in mid-20th-century films and stage productions.
  • B. Ron Saunders chosen
    Ron Saunders was an English football manager best known for leading Aston Villa to major domestic success, including the First Division title in 1980–81.
  • C. Ronald Bailey
    Ronald Bailey is a family member of Pro Football Hall of Fame cornerback Champ Bailey.
  • D. Rod Liddle
    Rod Liddle is a British journalist and commentator known for his provocative columns and outspoken views on politics and culture.
  • E. Jeremy Saunders
    Jeremy Saunders is a recurring fictional character in Satyajit Ray’s Bengali science-fiction “Professor Shonku” stories, typically appearing as an English associate in the professor’s adventurous experiments.
  • 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_69ca8433ec308190b8b25a6fe359c34c completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdeb2425008190a92c5148ed703d5c completed April 2, 2026, 4:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e603d4548190a561e735c603946f completed April 5, 2026, 10:45 p.m.
Created at: March 30, 2026, 9:07 p.m.