Triple

T15613067
Position Surface form Disambiguated ID Type / Status
Subject Swan Burnett E375345 entity
Predicate familyName P18 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: [Swan Burnett, familyName, Burnett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burnett
Context triple: [Swan Burnett, familyName, 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e8148a0819087d6d69cc84487ca completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f3913908190acdd7da62b4f521d completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:13 a.m.