Triple

T17146878
Position Surface form Disambiguated ID Type / Status
Subject Castilla del Oro E416112 entity
Predicate borderedBy P224 FINISHED
Object Veragua E810087 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: Veragua | Statement: [Castilla del Oro, borderedBy, Veragua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Veragua
Context triple: [Castilla del Oro, borderedBy, Veragua]
  • A. Veragua chosen
    Veragua was a historical territory in Central America associated with the hereditary dukedom granted to the descendants of Christopher Columbus under the title Duke of Veragua.
  • B. Tocaima
    Tocaima is a historic Colombian town in the Cundinamarca Department, known for its warm climate and thermal springs.
  • C. Chinchiná
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • D. Marulanda
    Marulanda is a small municipality and town located in the Caldas Department of Colombia, known for its rural Andean landscapes and agricultural economy.
  • E. Columbio
    Columbio is a rural municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and multicultural indigenous communities.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2db20d48190b5d69ccf89f3bc42 completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014158ed8c8190adb3c03c8a114a59 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:36 a.m.