Triple

T18316754
Position Surface form Disambiguated ID Type / Status
Subject Amazonas (Brazilian state) E438768 entity
Predicate hasMajorCity P316 FINISHED
Object Manacapuru 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: Manacapuru | Statement: [Amazonas (Brazilian state), hasMajorCity, Manacapuru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manacapuru
Context triple: [Amazonas (Brazilian state), hasMajorCity, Manacapuru]
  • A. Manacapuru chosen
    Manacapuru is a Brazilian city in the state of Amazonas, located near Manaus along the Amazon River and known as a regional commercial and ecological hub.
  • B. Aquiraz
    Aquiraz is a coastal municipality in the Brazilian state of Ceará known for its beaches, historical colonial architecture, and tourism attractions.
  • C. Camaçari
    Camaçari is an industrial city in the state of Bahia, Brazil, known for hosting one of the largest petrochemical complexes in the Southern Hemisphere.
  • D. Vitória da Conquista
    Vitória da Conquista is a major inland city in the state of Bahia, Brazil, known as a regional commercial, educational, and services hub in the country’s Northeast.
  • E. Parnamirim
    Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5021e61008190a300b6c51976a837 completed April 19, 2026, 4:26 p.m.
Created at: April 10, 2026, 10:36 a.m.