Triple

T1170084
Position Surface form Disambiguated ID Type / Status
Subject Pernambuco E24892 entity
Predicate hasCity P316 FINISHED
Object Olinda E25683 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: Olinda | Statement: [Pernambuco, hasCity, Olinda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olinda
Context triple: [Pernambuco, hasCity, Olinda]
  • A. Olinda chosen
    Olinda is a historic coastal city in northeastern Brazil renowned for its well-preserved colonial architecture and vibrant Carnival celebrations.
  • 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. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • D. Fortaleza
    Fortaleza is a large coastal city in northeastern Brazil known for its beaches, tourism, and role as the capital of the state of Ceará.
  • E. 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.
  • 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_69a4bce972cc8190bce0b77cfda6da41 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99730c408190a705ca67a6724778 completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:45 p.m.