Triple

T1643374
Position Surface form Disambiguated ID Type / Status
Subject Kazan E35521 entity
Predicate hasSisterCity P919 FINISHED
Object Porto Alegre E115361 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: Porto Alegre | Statement: [Kazan, hasSisterCity, Porto Alegre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto Alegre
Context triple: [Kazan, hasSisterCity, Porto Alegre]
  • A. Porto Alegre chosen
    Porto Alegre is the capital and largest city of Brazil’s southernmost state, Rio Grande do Sul, known for its cultural diversity, strong gaucho traditions, and important role as a regional economic and political center.
  • B. Curitiba
    Curitiba is the capital and largest city of the Brazilian state of Paraná, known for its innovative urban planning, extensive public transportation system, and high quality of life.
  • C. Belo Horizonte
    Belo Horizonte is the capital and largest city of the Brazilian state of Minas Gerais, known for its modernist architecture, surrounding mountains, and vibrant cultural and economic life.
  • D. Campinas
    Campinas is a major city in the state of São Paulo, Brazil, known as an important industrial, technological, and transportation hub in the country.
  • E. São Paulo
    São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3f4d8c8190aa0a44d1c9b1a7f0 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a0096c81909dc723d0db95481e completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.