Triple

T10128917
Position Surface form Disambiguated ID Type / Status
Subject Bogotá River E226284 entity
Predicate hasMouthNear P350 FINISHED
Object Girardot E33042 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: Girardot | Statement: [Bogotá River, hasMouthNear, Girardot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Girardot
Context triple: [Bogotá River, hasMouthNear, Girardot]
  • A. Girardot chosen
    Girardot is a Colombian city known as a major tourist and commercial center on the Magdalena River, popular for its warm climate and resort tourism.
  • B. Girardota
    Girardota is a municipality in the Antioquia Department of Colombia, located in the northern part of the Aburrá Valley metropolitan area near Medellín.
  • C. Manizales
    Manizales is a mountainous Colombian city known for its coffee production, cool climate, and location in the central Andes.
  • D. Montería
    Montería is a major Colombian city known as the capital of Córdoba Department, recognized for its cattle ranching economy and location along the Sinú River.
  • E. Cartagena del Chairá
    Cartagena del Chairá is a rural municipality in southern Colombia’s Caquetá Department, known for its Amazonian rainforest environment and history of armed conflict presence.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd333186c819088bbf617967f24fa completed April 2, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e5c29f6c8190b347a6963ca46dac completed April 5, 2026, 10:44 p.m.
Created at: March 30, 2026, 9:05 p.m.