Triple

T20492941
Position Surface form Disambiguated ID Type / Status
Subject Catalina y Sebastián E502792 entity
Predicate hasCastMember P2308 FINISHED
Object Guillermo Murray 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 Murray | Statement: [Catalina y Sebastián, hasCastMember, Guillermo Murray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guillermo Murray
Context triple: [Catalina y Sebastián, hasCastMember, Guillermo Murray]
  • A. Guillermo Murray chosen
    Guillermo Murray was an Argentine-born Mexican actor known for his prolific work in classic Mexican cinema and telenovelas.
  • B. 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.
  • C. 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.
  • D. Guillermo Brown
    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.
  • E. Louis Aguirre
    Louis Aguirre is an American television journalist and entertainment news anchor known for his work on national entertainment programs and local Miami newscasts.
  • 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_69e0b4b0373881909dd3e9387f82eab4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cbb3bd081909351525208b41bba completed April 20, 2026, 9:38 p.m.
Created at: April 16, 2026, 11:35 a.m.