Triple

T10587607
Position Surface form Disambiguated ID Type / Status
Subject Luis Colón de Toledo E249893 entity
Predicate historicalRegionOfActivity P13711 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: [Luis Colón de Toledo, historicalRegionOfActivity, Veragua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Veragua
Context triple: [Luis Colón de Toledo, historicalRegionOfActivity, 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5276b0ae48190b2935230363239e0 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b9440548190bff01847a940266b completed April 10, 2026, 7:12 p.m.
Created at: April 6, 2026, 12:40 p.m.