Triple

T9158236
Position Surface form Disambiguated ID Type / Status
Subject fourth voyage of Christopher Columbus E219757 entity
Predicate shipUsed P880 FINISHED
Object Vizcaína
Vizcaína was one of the ships in Christopher Columbus’s fourth voyage to the Americas in the early 16th century.
 E782749 NE FINISHED

How this triple was built (4 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: Vizcaína | Statement: [fourth voyage of Christopher Columbus, shipUsed, Vizcaína]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vizcaína
Context triple: [fourth voyage of Christopher Columbus, shipUsed, Vizcaína]
  • A. Caviahue
    Caviahue is a small Argentine town and ski resort in the Andes, known for its volcanic landscapes, thermal waters, and proximity to the Copahue volcano.
  • B. Ollagüe
    Ollagüe is a small high-altitude town and volcanic area in northern Chile near the Bolivian border, known for its Andean landscapes and proximity to active volcanoes.
  • C. Peñafiel
    Peñafiel is a historic town in Spain renowned for its medieval castle and wine-making tradition in the Ribera del Duero region.
  • D. Guayaramerín
    Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
  • E. Cañete
    Cañete is a coastal province and agricultural hub in central Peru, known for its fertile valleys, Afro-Peruvian cultural heritage, and production of crops like grapes and cotton.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Vizcaína
Triple: [fourth voyage of Christopher Columbus, shipUsed, Vizcaína]
Generated description
Vizcaína was one of the ships in Christopher Columbus’s fourth voyage to the Americas in the early 16th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vizcaína
Target entity description: Vizcaína was one of the ships in Christopher Columbus’s fourth voyage to the Americas in the early 16th century.
  • A. Caviahue
    Caviahue is a small Argentine town and ski resort in the Andes, known for its volcanic landscapes, thermal waters, and proximity to the Copahue volcano.
  • B. Ollagüe
    Ollagüe is a small high-altitude town and volcanic area in northern Chile near the Bolivian border, known for its Andean landscapes and proximity to active volcanoes.
  • C. Peñafiel
    Peñafiel is a historic town in Spain renowned for its medieval castle and wine-making tradition in the Ribera del Duero region.
  • D. Guayaramerín
    Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
  • E. Cañete
    Cañete is a coastal province and agricultural hub in central Peru, known for its fertile valleys, Afro-Peruvian cultural heritage, and production of crops like grapes and cotton.
  • F. None of above. chosen

Provenance (5 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_69ca83e25418819093c6503deeaf30de completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca9d6b9ac819094efe12c1ed67ecf completed April 1, 2026, 5:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05468843481908a1f17219a1bfc79 completed April 3, 2026, 11:59 p.m.
NEDg Description generation batch_69d0554fda40819083ef2d13d6fba905 completed April 4, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_69d055ca4fc08190b30e1b31ded51189 completed April 4, 2026, 12:05 a.m.
Created at: March 30, 2026, 7:21 p.m.