Triple

T17682230
Position Surface form Disambiguated ID Type / Status
Subject Buxton family E440797 entity
Predicate hasNotableMember P304 FINISHED
Object Charles Buxton NE NERFINISHED

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: Charles Buxton | Statement: [Buxton family, hasNotableMember, Charles Buxton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Buxton
Context triple: [Buxton family, hasNotableMember, Charles Buxton]
  • A. Charles Buxton chosen
    Charles Buxton was a 19th-century English brewer, philanthropist, and Liberal politician known for his social reform efforts and public service.
  • B. Edward North Buxton
    Edward North Buxton was a British conservationist, politician, and big-game hunter known for his efforts to protect African wildlife and natural landscapes.
  • C. John Blatchley
    John Blatchley was a British theatre director and educator best known as a co-founder of the influential Drama Centre London acting school.
  • D. William Gaxton
    William Gaxton was an American stage and film actor best known for his leading roles in Broadway musical comedies during the early to mid-20th century.
  • E. George Dickerson
    George Dickerson was an American actor and writer best known for his supporting roles in films of the 1980s and 1990s, as well as for his work in television and theater.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4704514d481908aad4172fa930e6b completed April 19, 2026, 6:03 a.m.
Created at: April 10, 2026, 10:02 a.m.