Triple

T5945177
Position Surface form Disambiguated ID Type / Status
Subject Universidad de la República (Uruguay) E132261 entity
Predicate foundingLocation P40 FINISHED
Object Montevideo E47651 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: Montevideo | Statement: [Universidad de la República (Uruguay), foundingLocation, Montevideo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montevideo
Context triple: [Universidad de la República (Uruguay), foundingLocation, Montevideo]
  • A. Montevideo chosen
    Montevideo is the capital and largest city of Uruguay, serving as the country’s main political, economic, and cultural center.
  • B. Buenos Aires
    Buenos Aires is the capital and largest city of Argentina, known for its rich European-influenced culture, tango music and dance, and vibrant urban life.
  • C. Ciudad del Este
    Ciudad del Este is a major commercial city in eastern Paraguay, known as a busy border trading hub near the tri-border area with Brazil and Argentina.
  • D. Bahía Blanca
    Bahía Blanca is a major port city in southern Buenos Aires Province, Argentina, known for its industrial activity and strategic location on the Atlantic coast.
  • E. Caxias do Sul
    Caxias do Sul is a major city in southern Brazil known for its strong European immigrant heritage, particularly German and Italian influences, and its significant industrial and wine-producing sectors.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0393a10448190b0960f4487e87448 completed March 22, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d2e42c88190927bba51caec186f completed March 24, 2026, 4:03 a.m.
Created at: March 22, 2026, 4:01 p.m.