Triple

T8436366
Position Surface form Disambiguated ID Type / Status
Subject Bahia E199233 entity
Predicate contains P35 FINISHED
Object Porto Seguro
Porto Seguro is a historic coastal city in northeastern Brazil, known as one of the first landing sites of Portuguese explorers and today a popular beach tourism destination.
E733760 NE FINISHED

How this triple was built (4 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: Porto Seguro | Statement: [Bahia, contains, Porto Seguro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto Seguro
Context triple: [Bahia, contains, Porto Seguro]
  • A. São Salvador do Mundo
    São Salvador do Mundo is a municipality on Santiago Island in Cape Verde, known for its rural communities and mountainous inland landscapes.
  • B. São Sebastião
    São Sebastião is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
  • C. São Sebastião
    São Sebastião is a coastal municipality in the state of São Paulo, Brazil, known for its beaches, tourism, and role as a port city.
  • D. Port of Salvador
    The Port of Salvador is a major Brazilian seaport and cargo hub on the Atlantic coast, serving as a key gateway for trade in northeastern Brazil.
  • E. Porto dos Casais
    Porto dos Casais was the original colonial settlement that later developed into the Brazilian city of Porto Alegre.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Porto Seguro
Triple: [Bahia, contains, Porto Seguro]
Generated description
Porto Seguro is a historic coastal city in northeastern Brazil, known as one of the first landing sites of Portuguese explorers and today a popular beach tourism destination.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Porto Seguro
Target entity description: Porto Seguro is a historic coastal city in northeastern Brazil, known as one of the first landing sites of Portuguese explorers and today a popular beach tourism destination.
  • A. São Salvador do Mundo
    São Salvador do Mundo is a municipality on Santiago Island in Cape Verde, known for its rural communities and mountainous inland landscapes.
  • B. São Sebastião
    São Sebastião is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
  • C. São Sebastião
    São Sebastião is a coastal municipality in the state of São Paulo, Brazil, known for its beaches, tourism, and role as a port city.
  • D. Port of Salvador
    The Port of Salvador is a major Brazilian seaport and cargo hub on the Atlantic coast, serving as a key gateway for trade in northeastern Brazil.
  • E. Porto dos Casais
    Porto dos Casais was the original colonial settlement that later developed into the Brazilian city of Porto Alegre.
  • F. None of above. chosen

Provenance (5 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe132a6f881908f990089792fccc4 completed March 31, 2026, 2:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d7d19608190ad3160fc00f8d4b0 completed April 2, 2026, 7:40 a.m.
NEDg Description generation batch_69ce1ea3aaf881909562b65cefb20089 completed April 2, 2026, 7:45 a.m.
NED2 Entity disambiguation (via description) batch_69ce1f8d748c81909b331ed822919447 completed April 2, 2026, 7:49 a.m.
Created at: March 30, 2026, 6:08 p.m.