Triple

T6093582
Position Surface form Disambiguated ID Type / Status
Subject Bolívar Department E135824 entity
Predicate contains P35 FINISHED
Object Magangué E481842 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: Magangué | Statement: [Bolívar Department, contains, Magangué]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magangué
Context triple: [Bolívar Department, contains, Magangué]
  • A. Magangué chosen
    Magangué is a Colombian city located in the department of Bolívar, known as an important commercial and river port along the Magdalena River.
  • B. Tucupita
    Tucupita is a small Venezuelan city that serves as the capital of Delta Amacuro state and the main urban center near the Orinoco Delta.
  • C. Rurrenabaque
    Rurrenabaque is a small Bolivian town known as a popular gateway to the Amazon rainforest and nearby Madidi National Park.
  • D. Nova Mamoré
    Nova Mamoré is a municipality in the Brazilian state of Rondônia, located in the western Amazon region near the border with Bolivia.
  • E. Sibaté
    Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
  • 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c057ac8c7481909fb22cf157be45ce completed March 22, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c125365a7481909e40d01c2d3590aa completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:12 p.m.