Triple

T8544820
Position Surface form Disambiguated ID Type / Status
Subject Bernabé Martí E202291 entity
Predicate name P16 FINISHED
Object Bernabé Martí E202291 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: Bernabé Martí | Statement: [Bernabé Martí, name, Bernabé Martí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bernabé Martí
Context triple: [Bernabé Martí, name, Bernabé Martí]
  • A. Bernabé Martí chosen
    Bernabé Martí was a Spanish operatic tenor known for his international career and for being married to soprano Montserrat Caballé.
  • B. Bernat Vilaplana
    Bernat Vilaplana is a Spanish film editor known for his frequent collaborations with director Guillermo del Toro on acclaimed films such as Pan’s Labyrinth.
  • C. Josep Batlló i Casanovas
    Josep Batlló i Casanovas was a wealthy Catalan industrialist best known as the patron who commissioned Antoni Gaudí to remodel Barcelona’s iconic Casa Batlló.
  • D. Antonio Miró
    Antonio Miró was an architect known for his work on prominent public buildings in Puerto Rico, including the design of the Puerto Rico Capitol.
  • E. Francesc Guàrdia i Vial
    Francesc Guàrdia i Vial was a Catalan architect associated with the early 20th-century Modernisme movement, known for designing prominent public buildings in Spain.
  • 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_69ca832461e88190a654c5e44e233aa8 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6e4e21c8190afcbca73713a5fa8 completed March 31, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea86036a881909cd1744cdb5b7a7f completed April 2, 2026, 5:33 p.m.
Created at: March 30, 2026, 6:18 p.m.