Triple

T2572840
Position Surface form Disambiguated ID Type / Status
Subject Colombian Caribbean region E57702 entity
Predicate majorPortCity P2994 FINISHED
Object Barranquilla E73884 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: Barranquilla | Statement: [Colombian Caribbean region, majorPortCity, Barranquilla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barranquilla
Context triple: [Colombian Caribbean region, majorPortCity, Barranquilla]
  • A. Barranquilla chosen
    Barranquilla is a major port city on Colombia’s Caribbean coast, known for its vibrant culture and famous Carnival festival.
  • B. Bucaramanga
    Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
  • C. Santa Marta
    Santa Marta is a historic Caribbean port city in northern Colombia and one of the oldest surviving Spanish settlements in South America.
  • D. Medellín
    Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
  • E. Pereira
    Pereira is a major Colombian city known as the capital of the Risaralda department and an important economic and cultural center in the country's coffee-growing region.
  • 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_69ab4a51410081908501dcf8bad9adc4 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3853c848190970e8a2da16d726d completed March 7, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa046b09c8190a03f6a24ae1a1d6e completed March 10, 2026, 4:38 a.m.
Created at: March 6, 2026, 9:48 p.m.