Triple

T15735995
Position Surface form Disambiguated ID Type / Status
Subject Mónica Cruz E381471 entity
Predicate hasRelative P367 FINISHED
Object Penélope Cruz E71824 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: Penélope Cruz | Statement: [Mónica Cruz, hasRelative, Penélope Cruz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Penélope Cruz
Context triple: [Mónica Cruz, hasRelative, Penélope Cruz]
  • A. Penélope Cruz chosen
    Penélope Cruz is an acclaimed Spanish actress known for her versatile performances in both European and Hollywood cinema, including collaborations with director Pedro Almodóvar and roles in films such as "Vicky Cristina Barcelona."
  • B. Paz Vega
    Paz Vega is a Spanish actress known for her roles in films such as "Sex and Lucía," "Spanglish," and various international productions.
  • C. Mónica Bardem
    Mónica Bardem is a Spanish actress and member of the Bardem family, known for her work in film and television.
  • D. Kate del Castillo
    Kate del Castillo is a Mexican actress best known internationally for her leading roles in telenovelas and the crime drama series "La Reina del Sur."
  • E. Pilar Bardem
    Pilar Bardem was a Spanish actress and prominent member of the Bardem acting family, known for her extensive film and television career and her activism.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd586a88190aa1b1b88368d386f completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8769aaac8190b41141eaa5ac6944 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:46 a.m.