Triple

T17707987
Position Surface form Disambiguated ID Type / Status
Subject Nick Spano E441481 entity
Predicate portrayed P1668 FINISHED
Object Javier 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: Javier | Statement: [Nick Spano, portrayed, Javier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Javier
Context triple: [Nick Spano, portrayed, Javier]
  • A. Javier chosen
    Javier is a masculine given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
  • B. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • C. Jorge
    Jorge is the given name of the renowned Argentine writer and poet Jorge Luis Borges, a central figure in 20th-century literature.
  • D. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • E. Jorge
    Jorge is a fictional character who appears in the Mexican film "Viridiana," directed by Luis Buñuel.
  • 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e472990b5c81908e0414d3230f283e completed April 19, 2026, 6:13 a.m.
Created at: April 10, 2026, 10:05 a.m.