Triple

T17213804
Position Surface form Disambiguated ID Type / Status
Subject Episode 4: The Deep South E417800 entity
Predicate setIn P1393 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: [Episode 4: The Deep South, setIn, Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brazil
Context triple: [Episode 4: The Deep South, setIn, 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dc795d08190b90801a4f8b23afe completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170eb9954819085e8c078cf137dc5 completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:38 a.m.