Triple

T22816916
Position Surface form Disambiguated ID Type / Status
Subject Kermit Erasmus E565122 entity
Predicate fullName P16 FINISHED
Object Kermit Romeo Erasmus 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: Kermit Romeo Erasmus | Statement: [Kermit Erasmus, fullName, Kermit Romeo Erasmus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kermit Romeo Erasmus
Context triple: [Kermit Erasmus, fullName, Kermit Romeo Erasmus]
  • A. Kermit Erasmus chosen
    Kermit Erasmus is a South African professional soccer player known as a forward who has played for clubs in South Africa and Europe as well as the national team.
  • B. Kermit Bloomgarden
    Kermit Bloomgarden was a prominent American theatrical producer best known for staging major mid-20th-century Broadway plays and musicals, including works by Arthur Miller.
  • C. Kermit Gordon
    Kermit Gordon was an American economist and public official who served as director of the U.S. Bureau of the Budget under Presidents John F. Kennedy and Lyndon B. Johnson.
  • D. Kermit Zarley
    Kermit Zarley is a former American professional golfer best known for his long PGA Tour career and later work as a Christian author.
  • E. Kermit Maynard
    Kermit Maynard was an American actor and stuntman best known for his roles in Western films during the 1930s and 1940s.
  • 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_69e2458426188190b58b8ab4844fe420 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17dcc41ac81908167856be021ea24 completed April 29, 2026, 3:41 a.m.
Created at: April 17, 2026, 3:33 p.m.