Triple

T5495628
Position Surface form Disambiguated ID Type / Status
Subject Cuiabá E144203 entity
Predicate hasStadium P105 FINISHED
Object Arena Pantanal E209285 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: Arena Pantanal | Statement: [Cuiabá, hasStadium, Arena Pantanal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arena Pantanal
Context triple: [Cuiabá, hasStadium, Arena Pantanal]
  • A. Arena Pantanal chosen
    Arena Pantanal is a multi-purpose football stadium in Cuiabá, Brazil, built and used as one of the host venues for the 2014 FIFA World Cup.
  • B. Farroupilha Park
    Farroupilha Park is a large, historic urban park and popular recreational area in Porto Alegre, Brazil, known for its green spaces, cultural events, and public gatherings.
  • C. Campo Grande park
    Campo Grande park is a large, historic urban green space in Valladolid, Spain, known for its landscaped gardens, ponds, and diverse birdlife.
  • D. Arena da Amazônia
    Arena da Amazônia is a modern football stadium in Manaus, Brazil, known for its distinctive rainforest-inspired design and role as a host venue during the 2014 FIFA World Cup.
  • E. Pantanal
    The Pantanal is one of the world’s largest tropical wetlands, renowned for its extraordinary biodiversity and vast seasonally flooded plains in central 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_69c008f5a2748190bce7a39aabf87a6d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01b8c05ac8190999f84c33719d794 completed March 22, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027887dc48190be1761b17481e106 completed March 22, 2026, 5:31 p.m.
Created at: March 22, 2026, 3:31 p.m.