Triple

T3717628
Position Surface form Disambiguated ID Type / Status
Subject municipal council of Gernika-Lumo E81568 entity
Predicate governs P760 FINISHED
Object Gernika-Lumo E97708 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: Gernika-Lumo | Statement: [municipal council of Gernika-Lumo, governs, Gernika-Lumo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gernika-Lumo
Context triple: [municipal council of Gernika-Lumo, governs, Gernika-Lumo]
  • A. Gernika-Lumo chosen
    Gernika-Lumo is a historic town in the Basque Country of northern Spain, internationally known for the 1937 bombing that inspired Pablo Picasso’s famous painting "Guernica."
  • B. de Garnica
    De Garnica is a Spanish surname associated with individuals such as José de Garnica.
  • C. Aramburu
    Aramburu is a Spanish-language surname of Basque origin borne by various notable figures in politics, religion, and sports.
  • D. Prado
    Prado is a neighborhood within the Brazilian city of Recife, known for its urban residential character and local commerce.
  • E. Ontinyent
    Ontinyent is a historic town in eastern Spain known for its textile industry, traditional festivals, and scenic setting along the Clariano River.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9d087c881909f6d2ec6e518fb02 completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db0ba70481908dfd11ee5c89faff completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:33 p.m.