Triple

T10930262
Position Surface form Disambiguated ID Type / Status
Subject Martín Alonso Pinzón E258183 entity
Predicate ship P880 FINISHED
Object Pinta E43365 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: Pinta | Statement: [Martín Alonso Pinzón, ship, Pinta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinta
Context triple: [Martín Alonso Pinzón, ship, Pinta]
  • A. Pinta chosen
    Pinta was one of the three ships in Christopher Columbus's 1492 expedition that led to the European discovery of the Americas.
  • B. Pinta Island
    Pinta Island is a remote, uninhabited island in Ecuador’s Galápagos archipelago, best known as the former home of Lonesome George, the last known Pinta Island tortoise.
  • C. Fernandina de Jagua
    Fernandina de Jagua was the original colonial name of the Cuban city now known as Cienfuegos, an important port on the island’s southern coast.
  • D. Guane
    Guane is a small town and municipality in western Cuba known for its rural character and tobacco-growing traditions.
  • E. Guane
    Guane is a small, historic village in Colombia’s Santander department, known for its preserved colonial architecture and tranquil rural atmosphere.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7709f92088190a15ae3638d3b14fb completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2175711d4819088f93bdf64ba4d3f completed April 17, 2026, 11:19 a.m.
Created at: April 8, 2026, 9:22 p.m.