Triple

T1172550
Position Surface form Disambiguated ID Type / Status
Subject Paraíba E24946 entity
Predicate hasCity P316 FINISHED
Object Campina Grande E149957 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: Campina Grande | Statement: [Paraíba, hasCity, Campina Grande]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Campina Grande
Context triple: [Paraíba, hasCity, Campina Grande]
  • A. Campina Grande chosen
    Campina Grande is a major city in northeastern Brazil known for its technology and education hubs and for hosting one of the world’s largest São João (June) festivals.
  • B. Petrolina
    Petrolina is a major city in northeastern Brazil known for its irrigated fruit production and location along the São Francisco River.
  • C. Recife
    Recife is a major coastal city in northeastern Brazil known for its historic colonial architecture, extensive waterways, and role as an important cultural and economic center.
  • D. João Pessoa
    João Pessoa is the capital and largest city of the Brazilian state of Paraíba, known for its historic colonial architecture and easternmost location in the Americas.
  • E. Vitória de Santo Antão
    Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcecab688190b21a926874cd98d1 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf15b1e08190a9c75bc7bc467197 completed March 8, 2026, 12:13 a.m.
Created at: March 1, 2026, 7:45 p.m.