Triple

T9293200
Position Surface form Disambiguated ID Type / Status
Subject Viridiana E223571 entity
Predicate hasCastMember P2308 FINISHED
Object Fernando Rey E502114 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: Fernando Rey | Statement: [Viridiana, hasCastMember, Fernando Rey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fernando Rey
Context triple: [Viridiana, hasCastMember, Fernando Rey]
  • A. Fernando Rey chosen
    Fernando Rey was a distinguished Spanish actor renowned for his sophisticated screen presence and memorable roles in European and international cinema, including collaborations with director Luis Buñuel.
  • B. Francisco Rabal
    Francisco Rabal was a renowned Spanish actor known for his powerful performances in European cinema, particularly in the mid-20th century.
  • C. Sabás Marín
    Sabás Marín was a Spanish military officer and colonial administrator who served as Captain General and governor of Cuba in the late 19th century.
  • D. Fernando Lamas
    Fernando Lamas was an Argentine-American actor and director known for his suave, romantic leading roles in Hollywood films of the 1950s.
  • E. Emilio Pérez Touriño
    Emilio Pérez Touriño is a Spanish economist and politician who served as president of the autonomous community of Galicia.
  • 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_69ca8422ddf881908a3f8f876c9f53aa completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0898b3288190a627a58bfd9c57fe completed April 1, 2026, 11:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0c766fb408190a9f073f033652b6f completed April 4, 2026, 8:10 a.m.
Created at: March 30, 2026, 7:35 p.m.