Triple

T15104014
Position Surface form Disambiguated ID Type / Status
Subject María Isabel Verdú Rollán E360741 entity
Predicate stageName P7872 FINISHED
Object Maribel Verdú E72383 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: Maribel Verdú | Statement: [María Isabel Verdú Rollán, stageName, Maribel Verdú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maribel Verdú
Context triple: [María Isabel Verdú Rollán, stageName, Maribel Verdú]
  • A. Maribel Verdú chosen
    Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
  • B. Ana Torrent
    Ana Torrent is a Spanish actress best known for her acclaimed childhood performances in films like "The Spirit of the Beehive" and "Cría cuervos."
  • C. Sara Montiel
    Sara Montiel was a celebrated Spanish actress and singer who became an international film star and cultural icon in the mid-20th century.
  • D. Marta Curro
    Marta Curro is an American former actress best known as the first wife of stage and screen actor Jerry Orbach.
  • E. Blanca Parés
    Blanca Parés is a Spanish actress best known for her role in Pedro Almodóvar’s acclaimed film "Julieta."
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00551521c8190b48d1a074bb4bdfc completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa92b99c48190b76e1306cf32a568 completed May 9, 2026, 9:37 p.m.
Created at: April 10, 2026, 3:05 a.m.