Triple

T1513414
Position Surface form Disambiguated ID Type / Status
Subject Mercedes Barcha E32064 entity
Predicate residence P75 FINISHED
Object Barranquilla, Colombia 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, Colombia | Statement: [Mercedes Barcha, residence, Barranquilla, Colombia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barranquilla, Colombia
Context triple: [Mercedes Barcha, residence, Barranquilla, Colombia]
  • A. Barranquilla chosen
    Barranquilla is a major port city on Colombia’s Caribbean coast, known for its vibrant culture and famous Carnival festival.
  • B. Cartagena, Colombia
    Cartagena, Colombia is a historic Caribbean port city famed for its well-preserved colonial walled old town, vibrant culture, and role as a major tourist and cultural center in Colombia.
  • 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. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • 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_69a885e8caf88190a5fbb6159ce87786 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a907d901ac8190be55ed4bac609d1d completed March 5, 2026, 4:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad401616ec81908edd9dcb9f4a0184 completed March 8, 2026, 9:23 a.m.
Created at: March 4, 2026, 7:26 p.m.