Triple

T14779316
Position Surface form Disambiguated ID Type / Status
Subject Burny Mattinson E347349 entity
Predicate givenName P17 FINISHED
Object Burnett E76940 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: Burnett | Statement: [Burny Mattinson, givenName, Burnett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burnett
Context triple: [Burny Mattinson, givenName, Burnett]
  • A. Burnett chosen
    Burnett is a surname most famously associated with American comedian and actress Carol Burnett, a pioneering figure in television sketch comedy.
  • B. Burnet
    Burnet is the middle name of William Burnet Tuthill, the American architect best known for designing New York’s Carnegie Hall.
  • C. Burnet
    Burnet is a small central Texas city that serves as the administrative and commercial hub of Burnet County.
  • D. Brewster
    Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
  • E. Brewster
    Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deca9c7cac8190ba900df95e42e318 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0d00d46c8190b6289a9b8511a8fb completed May 8, 2026, 4:19 p.m.
Created at: April 10, 2026, 1:31 a.m.