Triple

T6299253
Position Surface form Disambiguated ID Type / Status
Subject Pacatuba E141209 entity
Predicate borderedBy P224 FINISHED
Object Horizonte E141208 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: Horizonte | Statement: [Pacatuba, borderedBy, Horizonte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Horizonte
Context triple: [Pacatuba, borderedBy, Horizonte]
  • A. Horizonte chosen
    Horizonte is a municipality in the state of Ceará in northeastern Brazil, known for its growing industrial sector and proximity to the Fortaleza metropolitan area.
  • B. Terra da Garoa
    Terra da Garoa is a popular nickname for the Brazilian metropolis of São Paulo, alluding to its characteristic light, misty rain.
  • C. Tianguá
    Tianguá is a municipality in northeastern Brazil known for its location in the highlands of the state of Ceará and its role as a regional commercial and agricultural center.
  • D. Terra do Sal
    Terra do Sal is a nickname for Mossoró, a city in Brazil’s Rio Grande do Norte state known for its significant salt production.
  • E. Terra Chã
    Terra Chã is a civil parish on Terceira Island in the Azores, Portugal, forming part of the municipality of Angra do Heroísmo.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0643ddaa48190b3ea8061fc1d9dc4 completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5199612948190b5ab22cf401686c2 completed March 26, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:27 p.m.