Triple

T76486
Position Surface form Disambiguated ID Type / Status
Subject America/Bogota E1527 entity
Predicate city P40 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: [America/Bogota, city, Bogotá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogotá
Context triple: [America/Bogota, city, 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. Quito
    Quito is the high-altitude Andean city that serves as Ecuador’s political and cultural center, renowned for its well-preserved colonial historic center and dramatic mountain setting.
  • C. Guayaquil
    Guayaquil is a major Pacific port city in southwestern Ecuador and the country’s principal commercial and industrial center.
  • D. Santiago
    Santiago is the capital and primary economic, political, and cultural center of Chile, located in the country’s central valley.
  • E. Santiago de Veraguas
    Santiago de Veraguas is a principal urban and commercial center in western Panama and the capital of Veraguas Province.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f1d20b88190b66836cc018e52e1 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2bf646ce88190b7c48f66c786e6bd completed Feb. 28, 2026, 10:11 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.