Triple

T5212875
Position Surface form Disambiguated ID Type / Status
Subject Gulf of Urabá E117674 entity
Predicate hasMajorPort P942 FINISHED
Object Turbo, Antioquia E21376 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: Turbo, Antioquia | Statement: [Gulf of Urabá, hasMajorPort, Turbo, Antioquia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turbo, Antioquia
Context triple: [Gulf of Urabá, hasMajorPort, Turbo, Antioquia]
  • A. Turbo, Colombia chosen
    Turbo is a port town in Colombia’s Antioquia Department on the Caribbean coast, known as a key transit point near the Darién Gap where the Pan-American Highway remains discontinuous.
  • B. Quindío
    Quindío is a small, coffee-producing department in Colombia’s Andean region, known for its lush landscapes, coffee culture, and role in the UNESCO-listed Coffee Cultural Landscape.
  • C. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • D. Puerto Boyacá
    Puerto Boyacá is a Colombian river port town on the Magdalena River known for its oil industry and strategic commercial importance.
  • E. Southwestern Antioquia
    Southwestern Antioquia is a subregion of Colombia’s Antioquia Department known for its mountainous landscapes, coffee production, and small rural towns.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a730e6c8190ae6082da41ee592a completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefdee940819098e397ab50f57411 completed March 21, 2026, 7:22 p.m.
Created at: March 20, 2026, 1:47 p.m.