Triple

T11667278
Position Surface form Disambiguated ID Type / Status
Subject Smiley Burnette E277281 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: [Smiley Burnette, familyName, Burnett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burnett
Context triple: [Smiley Burnette, 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. Brewster
    Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
  • D. 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.
  • E. Brewster
    Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13b36ae4819096e6dfca23a69250 completed April 27, 2026, 7:43 a.m.
Created at: April 8, 2026, 9:39 p.m.