Triple

T10401296
Position Surface form Disambiguated ID Type / Status
Subject Região dos Lagos E245151 entity
Predicate contains P35 FINISHED
Object Saquarema
Saquarema is a coastal city in the state of Rio de Janeiro, Brazil, known for its beaches and strong surfing culture.
E872731 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: Saquarema | Statement: [Região dos Lagos, contains, Saquarema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saquarema
Context triple: [Região dos Lagos, contains, Saquarema]
  • A. Jacareí
    Jacareí is a municipality in southeastern Brazil known as part of the industrial and technological corridor within the state of São Paulo.
  • B. Macaé
    Macaé is a coastal city in southeastern Brazil known for its offshore oil industry and role as a major hub for petroleum exploration.
  • C. Cumbuco
    Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
  • D. Búzios
    Búzios is a popular Brazilian coastal resort town on the Atlantic Ocean, known for its beaches, nightlife, and upscale tourism.
  • E. Cabo Frio
    Cabo Frio is a coastal city in southeastern Brazil known for its white-sand beaches, clear waters, and tourism-driven economy.
  • 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: Saquarema
Triple: [Região dos Lagos, contains, Saquarema]
Generated description
Saquarema is a coastal city in the state of Rio de Janeiro, Brazil, known for its beaches and strong surfing culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Saquarema
Target entity description: Saquarema is a coastal city in the state of Rio de Janeiro, Brazil, known for its beaches and strong surfing culture.
  • A. Jacareí
    Jacareí is a municipality in southeastern Brazil known as part of the industrial and technological corridor within the state of São Paulo.
  • B. Macaé
    Macaé is a coastal city in southeastern Brazil known for its offshore oil industry and role as a major hub for petroleum exploration.
  • C. Cumbuco
    Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
  • D. Búzios
    Búzios is a popular Brazilian coastal resort town on the Atlantic Ocean, known for its beaches, nightlife, and upscale tourism.
  • E. Cabo Frio
    Cabo Frio is a coastal city in southeastern Brazil known for its white-sand beaches, clear waters, and tourism-driven economy.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9e2f11c8190b30695cba2975544 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d94af4ee6881909a36ee1a06a9d3e2 completed April 10, 2026, 7:09 p.m.
NEDg Description generation batch_69d94c6fa9ac8190819a399754d2bd15 completed April 10, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69d953440a508190a50d1897cdbeba03 completed April 10, 2026, 7:45 p.m.
Created at: April 6, 2026, 12:07 p.m.