Triple

T7316180
Position Surface form Disambiguated ID Type / Status
Subject José Gervasio Artigas E168417 entity
Predicate placeOfBirth P1 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: [José Gervasio Artigas, placeOfBirth, Montevideo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montevideo
Context triple: [José Gervasio Artigas, placeOfBirth, 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ef162d488190bf1c63b71b20a294 completed March 27, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa78d8e08190a5658f2df7fbf667 completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 3:02 p.m.