Triple

T22672937
Position Surface form Disambiguated ID Type / Status
Subject Nekane Amaya E560268 entity
Predicate worksFor P5820 FINISHED
Object Ertzaintza 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: Ertzaintza | Statement: [Nekane Amaya, worksFor, Ertzaintza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ertzaintza
Context triple: [Nekane Amaya, worksFor, Ertzaintza]
  • A. Ertzaintza chosen
    Ertzaintza is the autonomous police force of Spain’s Basque Country, responsible for regional law enforcement and public security.
  • B. Guardia Civil
    The Guardia Civil is Spain’s historic national gendarmerie-style police force, known for its military structure and role in maintaining public order and rural security.
  • C. Mossos d'Esquadra
    Mossos d'Esquadra is the autonomous police force of Catalonia responsible for public security, law enforcement, and criminal investigation across the region.
  • D. Policía Nacional
    La Policía Nacional es un cuerpo de seguridad estatal de España encargado de funciones de policía judicial, control de fronteras, seguridad ciudadana e investigación de delitos en el ámbito urbano.
  • E. Guàrdia
    Guàrdia is a Catalan surname associated with figures such as the architect Francesc Guàrdia i Vial.
  • 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_69e2454bfd00819099115715a22cb057 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17821daf88190b18a73a222fc22fb completed April 29, 2026, 3:16 a.m.
Created at: April 17, 2026, 3:10 p.m.