Triple

T8027301
Position Surface form Disambiguated ID Type / Status
Subject Columba Bush E186886 entity
Predicate familyName P18 FINISHED
Object Garnica E228192 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: Garnica | Statement: [Columba Bush, familyName, Garnica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garnica
Context triple: [Columba Bush, familyName, Garnica]
  • A. de Garnica chosen
    De Garnica is a Spanish surname associated with individuals such as José de Garnica.
  • B. Gernika-Lumo
    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."
  • C. Albuhera
    Albuhera is a village in southwestern Spain that was the site of a major 1811 Peninsular War battle between British-led allied forces and the French.
  • D. Gironella
    Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
  • E. Manresa
    Manresa is a historic city in Catalonia, Spain, known for its medieval architecture and significance as a religious and commercial center in the region.
  • 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_69ca82ad4e2c8190a693e3c9e30fe66f completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3eccacb0819082f7c3d6fd48e3c4 completed March 31, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56da597c8190931091482d60b0a6 completed March 31, 2026, 11:20 p.m.
Created at: March 30, 2026, 5:21 p.m.