Triple

T23224116
Position Surface form Disambiguated ID Type / Status
Subject Dandara dos Palmares E580971 entity
Predicate hasGivenName P17 FINISHED
Object Dandara NE NERFINISHED

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: Dandara | Statement: [Dandara dos Palmares, hasGivenName, Dandara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dandara
Context triple: [Dandara dos Palmares, hasGivenName, Dandara]
  • A. Dandara
    Dandara is a UK-based property development company known for building residential and mixed-use projects across various regions.
  • B. Dandara dos Palmares chosen
    Dandara dos Palmares was a 17th-century Afro-Brazilian warrior and leader who played a key role in the resistance against slavery in the Quilombo dos Palmares.
  • C. Igarassu
    Igarassu is one of Brazil’s oldest colonial towns, known for its historic churches and coastal location in the northeastern state of Pernambuco.
  • D. Oriximiná
    Oriximiná is a large municipality in the Brazilian state of Pará, known for its Amazon rainforest areas, river systems, and significant mining and conservation sites.
  • E. Igaratá
    Igaratá is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and reservoir that attracts tourism and outdoor recreation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e246043c48819089bae72c9a9c306c completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f1922b4a348190ae570a869e30059f completed April 29, 2026, 5:07 a.m.
Created at: April 17, 2026, 4:08 p.m.