Triple

T14411724
Position Surface form Disambiguated ID Type / Status
Subject Maribel Verdú E357342 entity
Predicate familyName P18 FINISHED
Object Verdú E357342 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: 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. Verdú chosen
    Verdú is a Spanish surname most notably borne by acclaimed film and television actress Maribel Verdú.
  • B. 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.
  • C. Dumbría
    Dumbría is a small municipality in the province of A Coruña in Galicia, northwestern Spain, known for its rural landscapes and proximity to the rugged Atlantic coastline.
  • D. Iadera
    Iadera is the ancient Roman and medieval Latin name for the coastal city now known as Zadar in Croatia.
  • E. Liria
    Liria is a historic town in the Valencian Community of Spain, known for its ancient Iberian and Roman heritage and its role as a noble title’s namesake.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90c9b3448190aec1608836a5e913 completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55269d8c81909592277741a93db6 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.