Triple

T22709473
Position Surface form Disambiguated ID Type / Status
Subject Cristina Iglesias E561554 entity
Predicate hasSpouse P13 FINISHED
Object Juan Muñoz 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: Juan Muñoz | Statement: [Cristina Iglesias, hasSpouse, Juan Muñoz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juan Muñoz
Context triple: [Cristina Iglesias, hasSpouse, Juan Muñoz]
  • A. Juan Muñoz chosen
    Juan Muñoz was a prominent Spanish sculptor and installation artist known for his enigmatic figurative works and influential role in late 20th-century contemporary art.
  • B. Miguel Ángel Jiménez
    Miguel Ángel Jiménez is a Spanish professional golfer renowned on the European Tour for his multiple tournament victories, distinctive personality, and remarkable longevity in the sport.
  • C. Juan Miguel Azpiroz
    Juan Miguel Azpiroz is a cinematographer best known for his work on the film "The Way."
  • D. Eduard Fernández
    Eduard Fernández is a Spanish actor known for his intense and versatile performances in film, television, and theater.
  • E. Javier Molinero
    Javier Molinero is a Spanish professional tennis player who has competed primarily on the ATP Challenger and ITF Futures circuits.
  • 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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f178d1e24881909ebd4531c0daef7f completed April 29, 2026, 3:19 a.m.
Created at: April 17, 2026, 3:17 p.m.