Triple

T17838087
Position Surface form Disambiguated ID Type / Status
Subject Guillermo Brown E445445 entity
Predicate name P16 FINISHED
Object Guillermo Brown 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: Guillermo Brown | Statement: [Guillermo Brown, name, Guillermo Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guillermo Brown
Context triple: [Guillermo Brown, name, Guillermo Brown]
  • A. Guillermo Brown chosen
    Guillermo Brown was an Irish-born Argentine admiral who is celebrated as the father of the Argentine Navy and a key figure in the country’s early naval victories.
  • B. Guillermo Miller
    Guillermo Miller was a prominent British-born military officer who played a key role in Peru’s struggle for independence in the early 19th century.
  • C. Guillermo Billinghurst
    Guillermo Billinghurst was a Peruvian politician who served as President of Peru in the early 20th century and was known for his populist and reformist agenda.
  • D. Guillermo Valentiner
    Guillermo Valentiner is a Venezuelan football executive best known as the founder of Caracas Fútbol Club, one of the country’s most prominent soccer teams.
  • E. Luis Godoy
    Luis Godoy is a personal name shared by several individuals, most commonly found in Spanish-speaking countries and associated with various professional and cultural fields.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d29830c81909fa3ef5a352921b8 completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:16 a.m.