Triple

T3433039
Position Surface form Disambiguated ID Type / Status
Subject Maribel Verdú E72383 entity
Predicate familyName P18 FINISHED
Object Verdú
Verdú is a Spanish surname most notably borne by acclaimed film and television actress Maribel Verdú.
 E357342 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: Verdú | Statement: [Maribel Verdú, familyName, Verdú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Verdú
Context triple: [Maribel Verdú, familyName, Verdú]
  • A. Vivarais
    Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
  • B. Iadera
    Iadera is the ancient Roman and medieval Latin name for the coastal city now known as Zadar in Croatia.
  • C. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • D. Martos
    Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
  • E. Alajeró
    Alajeró is a small coastal and rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes and traditional Canarian character.
  • 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: Verdú
Triple: [Maribel Verdú, familyName, Verdú]
Generated description
Verdú is a Spanish surname most notably borne by acclaimed film and television actress Maribel Verdú.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Verdú
Target entity description: Verdú is a Spanish surname most notably borne by acclaimed film and television actress Maribel Verdú.
  • A. Vivarais
    Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
  • B. Iadera
    Iadera is the ancient Roman and medieval Latin name for the coastal city now known as Zadar in Croatia.
  • C. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • D. Martos
    Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
  • E. Alajeró
    Alajeró is a small coastal and rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes and traditional Canarian character.
  • F. None of above. chosen

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_69ad85ae14308190bcbc25cfa0246c0b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9c077d48190bee40795cab3e422 completed March 8, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3547d3f4c8190bc6811398bd8f080 completed March 13, 2026, 12:04 a.m.
NEDg Description generation batch_69b3566a6f3c8190a717deb08209c880 completed March 13, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_69b356f8f7648190b10e62990634af79 completed March 13, 2026, 12:14 a.m.
Created at: March 8, 2026, 3:15 p.m.