Triple

T22163585
Position Surface form Disambiguated ID Type / Status
Subject Sex and Lucia E547731 entity
Predicate starring P1507 FINISHED
Object Elena Anaya 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: Elena Anaya | Statement: [Sex and Lucia, starring, Elena Anaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elena Anaya
Context triple: [Sex and Lucia, starring, Elena Anaya]
  • A. Elena Anaya chosen
    Elena Anaya is a Spanish actress known for her roles in both European cinema and Hollywood productions, including prominent performances in films like "The Skin I Live In."
  • B. Blanca Suárez
    Blanca Suárez is a Spanish actress best known for her prominent roles in popular television series and films, becoming one of Spain’s most recognizable contemporary screen stars.
  • C. Ana de Armas
    Ana de Armas is a Cuban-Spanish actress known for her breakout roles in films such as "Blade Runner 2049," "Knives Out," and "Blonde."
  • D. Chimene Diaz
    Chimene Diaz is the older sister of American actress Cameron Diaz and is a non-celebrity who has largely stayed out of the public spotlight.
  • E. Úrsula Corberó
    Úrsula Corberó is a Spanish actress best known internationally for her role as Tokyo in the hit television series "Money Heist."
  • 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_69e11e3c4c5c81908d336165816b12e0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12a2f2f90819080b5bb73a6052c24 completed April 28, 2026, 9:44 p.m.
Created at: April 16, 2026, 8:34 p.m.