Triple

T1172549
Position Surface form Disambiguated ID Type / Status
Subject Paraíba E24946 entity
Predicate hasCity P316 FINISHED
Object João Pessoa E139248 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: João Pessoa | Statement: [Paraíba, hasCity, João Pessoa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: João Pessoa
Context triple: [Paraíba, hasCity, João Pessoa]
  • A. João Pessoa chosen
    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.
  • B. 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.
  • C. Belém
    Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
  • D. Mossoró
    Mossoró is a major city in northeastern Brazil known for its oil industry, salt production, and strong cultural traditions in the state of Rio Grande do Norte.
  • E. Olinda
    Olinda is a historic coastal city in northeastern Brazil renowned for its well-preserved colonial architecture and vibrant Carnival celebrations.
  • 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_69ac8a0646388190b440451d786db04c completed March 7, 2026, 8:26 p.m.
Created at: March 1, 2026, 7:45 p.m.