Triple

T16454483
Position Surface form Disambiguated ID Type / Status
Subject Francisca Villanova y Marco E399639 entity
Predicate residence P75 FINISHED
Object Bogotá E1526 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: Bogotá | Statement: [Francisca Villanova y Marco, residence, Bogotá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogotá
Context triple: [Francisca Villanova y Marco, residence, Bogotá]
  • A. Bogotá chosen
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • B. Bogotá and Medellín
    Bogotá and Medellín are Colombia’s two largest and most important cities, serving as major centers of politics, culture, and commerce in the country.
  • C. Cali
    Cali is a major city in southwestern Colombia known as an important economic center and the country’s capital of salsa.
  • D. Medellín
    Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
  • E. Medellín
    Medellín is a historic town in the Extremadura region of western Spain, known as the birthplace of conquistador Hernán Cortés and for its well-preserved medieval castle overlooking the Guadiana River.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7c84fc8190bcb0df96bdec647e completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f4e31a08190b121d0cfe2a406c2 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.