Triple

T10249767
Position Surface form Disambiguated ID Type / Status
Subject Kerr Smith E240309 entity
Predicate givenName P17 FINISHED
Object Kerr E93876 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: Kerr | Statement: [Kerr Smith, givenName, Kerr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerr
Context triple: [Kerr Smith, givenName, Kerr]
  • A. Kerr chosen
    Kerr is a surname of Scottish origin borne by numerous notable individuals across fields such as politics, academia, sports, and the arts.
  • B. Ker
    Ker is a variant form of the surname Kerr, which is of Scottish origin and historically associated with Border Reiver families.
  • C. Kaluza
    Kaluza is a surname most notably associated with Theodor Kaluza, the German physicist who proposed a unifying five-dimensional theory of gravity and electromagnetism.
  • D. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • E. Bardeen
    Bardeen is a surname most notably associated with John Bardeen, the American physicist who won the Nobel Prize in Physics twice for his work on the transistor and superconductivity.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d23c4cd88190b99e65a074b68d6b completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7b66c6881908b432fbdd5ecf11e completed April 9, 2026, 12:49 a.m.
Created at: April 6, 2026, 11:28 a.m.