Triple

T22494392
Position Surface form Disambiguated ID Type / Status
Subject Kenneth Lauren Burns E556100 entity
Predicate familyName P18 FINISHED
Object Burns 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: Burns | Statement: [Kenneth Lauren Burns, familyName, Burns]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burns
Context triple: [Kenneth Lauren Burns, familyName, Burns]
  • A. Burns chosen
    Burns is a common Scottish surname most famously associated with the poet Robert Burns.
  • B. Burns
    Burns is an electronic music producer and DJ known for his work in dance and pop music, including collaborations with major artists.
  • C. Burns
    Burns is a small city in Harney County, eastern Oregon, known as a remote high-desert community and regional service center for the surrounding ranching and natural resource areas.
  • D. Burn!
    Burn! is a 1969 political drama film directed by Gillo Pontecorvo that explores themes of colonialism and revolution through the story of a fictional Caribbean island.
  • E. Burned
    Burned is a mystery novel by American author Carol Higgins Clark, featuring her recurring sleuth Regan Reilly in a suspenseful, lighthearted whodunit.
  • 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_69e11e5445bc8190b6a9481926db3355 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15cb0dfb88190a4175e5e95d7ad4b completed April 29, 2026, 1:19 a.m.
Created at: April 16, 2026, 8:49 p.m.