Triple

T18648037
Position Surface form Disambiguated ID Type / Status
Subject Ronnie Brown E455854 entity
Predicate givenName P17 FINISHED
Object Ronnie 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: Ronnie | Statement: [Ronnie Brown, givenName, Ronnie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ronnie
Context triple: [Ronnie Brown, givenName, Ronnie]
  • A. Ronnie
    Ronnie is the central protagonist of the crime thriller film "Catch .44," around whom the movie’s violent, twisting plot revolves.
  • B. Ronnie chosen
    Ronnie is a masculine given name commonly used in English-speaking countries, often as a diminutive of Ronald or Veronica.
  • C. Ronny
    Ronny is a Malaysian-born comedian and actor best known as a correspondent on The Daily Show and for creating and starring in the sitcom Ronny Chieng: International Student.
  • D. Ronnie Hammond
    Ronnie Hammond was an American singer best known as the longtime lead vocalist for the Southern rock band Atlanta Rhythm Section.
  • E. Ronnie Fish
    Ronnie Fish is a recurring comic character in P. G. Wodehouse’s Blandings Castle stories, known as Lord Emsworth’s mischievous and often romantically entangled nephew.
  • 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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5500f007c81908b1835569be913d7 completed April 19, 2026, 9:58 p.m.
Created at: April 10, 2026, 11:47 a.m.