Triple

T5210031
Position Surface form Disambiguated ID Type / Status
Subject Burnside E117608 entity
Predicate hasNotableBearer P458 FINISHED
Object John Burnside E454243 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: John Burnside | Statement: [Burnside, hasNotableBearer, John Burnside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Burnside
Context triple: [Burnside, hasNotableBearer, John Burnside]
  • A. John Burnside chosen
    John Burnside is a Scottish poet, novelist, and essayist known for his lyrical explorations of nature, memory, and the uncanny in contemporary literature.
  • B. Doug Mahon
    Doug Mahon is a technology entrepreneur best known as a founder of the data storage company Seagate Technology.
  • C. John Callaghan
    John Callaghan is a relatively obscure individual whose name is notably recorded as a bearer of the surname Callaghan.
  • D. Brian Beattie
    Brian Beattie is an American musician, producer, and arranger known for his inventive orchestral and studio work with indie and alternative artists.
  • E. Murray Kinnell
    Murray Kinnell was an English-born character actor active in early 20th-century American cinema, known for his supporting roles in numerous Hollywood films of the 1930s and 1940s.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a703e388190845dedd17252ddde completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefd9e0b481908db7d6e2907b3b2b completed March 21, 2026, 7:22 p.m.
Created at: March 20, 2026, 1:47 p.m.