Triple

T12474215
Position Surface form Disambiguated ID Type / Status
Subject BHP Group E298134 entity
Predicate hasMajorOperationIn P95663 FINISHED
Object Brazil E19289 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: Brazil | Statement: [BHP Group, hasMajorOperationIn, Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brazil
Context triple: [BHP Group, hasMajorOperationIn, Brazil]
  • A. Brazil chosen
    Brazil is the largest country in South America, known for its vast Amazon rainforest, diverse culture, and major cities like São Paulo and Rio de Janeiro.
  • B. Brazil
    Brazil is a 1985 dystopian science fiction film known for its darkly satirical portrayal of a bureaucratic, totalitarian society and its distinctive, surreal visual style.
  • C. Brasyl
    Brasyl is a science fiction novel by Ian McDonald that intertwines multiple timelines in Brazil to explore themes of quantum reality, culture, and globalization.
  • D. Portela
    Portela is a residential parish in the municipality of Loures, within the Lisbon metropolitan area of Portugal.
  • E. Republic of the United States of Brazil
    The Republic of the United States of Brazil was the federal republican regime that succeeded the Brazilian monarchy in 1889 and governed Brazil through much of the 20th century.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcb194c81908b5e0320ddfd463c completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f16e87c8190b7e9f61561ae865a completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.