Triple

T8668652
Position Surface form Disambiguated ID Type / Status
Subject Guapimirim E205739 entity
Predicate borders P224 FINISHED
Object Magé E204806 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: Magé | Statement: [Guapimirim, borders, Magé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magé
Context triple: [Guapimirim, borders, Magé]
  • A. Magé chosen
    Magé is a municipality in the state of Rio de Janeiro, Brazil, located in the metropolitan region of Rio de Janeiro and known for its coastal setting and historical significance.
  • B. Mogi Guaçu
    Mogi Guaçu is a municipality in the interior of Brazil’s São Paulo state, known for its industrial activity and the Mogi Guaçu River that runs through it.
  • C. Itanhaém
    Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
  • D. Pau dos Ferros
    Pau dos Ferros is a municipality in the interior of Brazil’s Rio Grande do Norte state, known as a regional commercial and educational hub in the Alto Oeste Potiguar region.
  • E. Botucatu
    Botucatu is a municipality in southeastern Brazil known for its higher-education institutions, especially São Paulo State University (UNESP), and its surrounding sandstone cliffs and natural landscapes.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48a48b548190b78259072b1224ee completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf286a364c8190b7f4f9d8243e2548 completed April 3, 2026, 2:39 a.m.
Created at: March 30, 2026, 6:31 p.m.