Triple

T10660676
Position Surface form Disambiguated ID Type / Status
Subject Pilar Bardem E251214 entity
Predicate child P120 FINISHED
Object Mónica Bardem
Mónica Bardem is a Spanish actress and member of the Bardem family, known for her work in film and television.
 E251214 NE FINISHED

How this triple was built (4 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: Mónica Bardem | Statement: [Pilar Bardem, child, Mónica Bardem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mónica Bardem
Context triple: [Pilar Bardem, child, Mónica Bardem]
  • A. 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.
  • 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. Emilia Gorriarán
    Emilia Gorriarán was the mother of Cuban revolutionary figure Camilo Cienfuegos.
  • D. Ángela Molina
    Ángela Molina is a renowned Spanish actress known for her work in European art-house cinema and collaborations with prominent directors such as Luis Buñuel.
  • E. Maribel Verdú
    Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mónica Bardem
Triple: [Pilar Bardem, child, Mónica Bardem]
Generated description
Mónica Bardem is a Spanish actress and member of the Bardem family, known for her work in film and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mónica Bardem
Target entity description: Mónica Bardem is a Spanish actress and member of the Bardem family, known for her work in film and television.
  • A. Pilar Bardem chosen
    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.
  • 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. Emilia Gorriarán
    Emilia Gorriarán was the mother of Cuban revolutionary figure Camilo Cienfuegos.
  • D. Ángela Molina
    Ángela Molina is a renowned Spanish actress known for her work in European art-house cinema and collaborations with prominent directors such as Luis Buñuel.
  • E. Maribel Verdú
    Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
  • F. None of above.

Provenance (5 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6e017f97c8190b22765a6f1e6719d completed April 8, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d998af75588190bb9bb749460c5766 completed April 11, 2026, 12:41 a.m.
NEDg Description generation batch_69d99e8312188190bec3090f34a7b9b9 completed April 11, 2026, 1:06 a.m.
NED2 Entity disambiguation (via description) batch_69d99f50e0888190b8e7b2547e1526af completed April 11, 2026, 1:09 a.m.
Created at: April 8, 2026, 9:08 p.m.