Triple

T18891844
Position Surface form Disambiguated ID Type / Status
Subject Samu Castillejo E462108 entity
Predicate familyName P18 FINISHED
Object Azuaga 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: Azuaga | Statement: [Samu Castillejo, familyName, Azuaga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Azuaga
Context triple: [Samu Castillejo, familyName, Azuaga]
  • A. Azuaga chosen
    Azuaga is a municipality in southwestern Spain known for its historical architecture and rural setting within the Extremadura region.
  • B. Berruecos
    Berruecos is a locality in southwestern Colombia historically known as the site where independence leader Antonio José de Sucre was assassinated in 1830.
  • C. Berazategui
    Berazategui is a city in the Buenos Aires Province of Argentina, known as a suburban part of Greater Buenos Aires with both residential areas and industrial activity.
  • D. Baeza
    Baeza is a historic Andalusian town in southern Spain renowned for its well-preserved Renaissance architecture and status as a UNESCO World Heritage Site.
  • E. Arnedo
    Arnedo is a town in the La Rioja region of northern Spain, known historically for its footwear industry and its location amid the Cidacos River valley.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c47bbf908190b141e98e3468e908 completed April 20, 2026, 6:15 a.m.
Created at: April 10, 2026, 11:58 a.m.