Triple

T111216
Position Surface form Disambiguated ID Type / Status
Subject Guillermo Navarro E2251 entity
Predicate name P16 FINISHED
Object Guillermo Navarro E2251 NE FINISHED

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 Navarro | Statement: [Guillermo Navarro, name, Guillermo Navarro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guillermo Navarro
Context triple: [Guillermo Navarro, name, Guillermo Navarro]
  • A. Guillermo Navarro chosen
    Guillermo Navarro is an acclaimed Mexican cinematographer known for his visually striking work on films such as "Pan’s Labyrinth," "Pacific Rim," and collaborations with directors like Guillermo del Toro.
  • B. Jordi Fernández
    Jordi Fernández is a Spanish professional basketball coach known for his roles as an NBA assistant and international head coach, including leading the Canadian national team.
  • C. Juan Bohón
    Juan Bohón was a Spanish conquistador best known as the founder of the Chilean city of La Serena in the 16th century.
  • D. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • E. Carles Gil
    Carles Gil is a Spanish attacking midfielder best known as the creative playmaker and captain of the New England Revolution in Major League Soccer.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a24fcdaeb48190a2d796677e4b3281 completed Feb. 28, 2026, 2:15 a.m.
NER Named-entity recognition batch_69a256ec650c8190bee2067e37065527 completed Feb. 28, 2026, 2:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69a27c04949481908af8c8426789bc53 completed Feb. 28, 2026, 5:24 a.m.
Created at: Feb. 28, 2026, 2:20 a.m.