Triple

T659886
Position Surface form Disambiguated ID Type / Status
Subject La Ville Radieuse E11729 entity
Predicate influenced P9 FINISHED
Object Brasília E34115 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: Brasília | Statement: [La Ville Radieuse, influenced, Brasília]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brasília
Context triple: [La Ville Radieuse, influenced, Brasília]
  • A. Brasília chosen
    Brasília is the modernist-planned capital city of Brazil, known for its distinctive architecture and role as a major political and administrative center in South America.
  • B. Belém
    Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
  • C. Rio de Janeiro
    Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
  • D. São Paulo
    São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
  • E. Recife
    Recife is a major coastal city in northeastern Brazil known for its historic colonial architecture, extensive waterways, and role as an important cultural and economic center.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49fa83c6081909fb786d1773fa88c completed March 1, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c3963c588190b7116f3f7aad2687 completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:36 p.m.