Triple

T11795716
Position Surface form Disambiguated ID Type / Status
Subject Novo Hamburgo E280500 entity
Predicate hasDistrict P459 FINISHED
Object Santo Afonso
Santo Afonso is a residential district within the city of Novo Hamburgo in the state of Rio Grande do Sul, Brazil.
E947064 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: Santo Afonso | Statement: [Novo Hamburgo, hasDistrict, Santo Afonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santo Afonso
Context triple: [Novo Hamburgo, hasDistrict, Santo Afonso]
  • A. Santo Antônio
    Santo Antônio is a historic central neighborhood of Recife, Brazil, known for its colonial architecture, commercial activity, and cultural landmarks.
  • B. Santa Luzia
    Santa Luzia is a small fishing village in Portugal’s Algarve region, known for its traditional octopus fishing and tranquil coastal atmosphere.
  • C. Santa Luzia
    Santa Luzia is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
  • D. Conceição
    Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • E. San-São
    San-São is the traditional Brazilian football derby between São Paulo FC and Santos FC, known for its historic rivalries and memorable matches.
  • 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: Santo Afonso
Triple: [Novo Hamburgo, hasDistrict, Santo Afonso]
Generated description
Santo Afonso is a residential district within the city of Novo Hamburgo in the state of Rio Grande do Sul, Brazil.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Santo Afonso
Target entity description: Santo Afonso is a residential district within the city of Novo Hamburgo in the state of Rio Grande do Sul, Brazil.
  • A. Santo Antônio
    Santo Antônio is a historic central neighborhood of Recife, Brazil, known for its colonial architecture, commercial activity, and cultural landmarks.
  • B. Santa Luzia
    Santa Luzia is a small fishing village in Portugal’s Algarve region, known for its traditional octopus fishing and tranquil coastal atmosphere.
  • C. Santa Luzia
    Santa Luzia is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
  • D. Conceição
    Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • E. San-São
    San-São is the traditional Brazilian football derby between São Paulo FC and Santos FC, known for its historic rivalries and memorable matches.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a1cda0819092d66a82fd882786 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0911c2a40819088079fc286e4dc67 completed April 28, 2026, 10:51 a.m.
NEDg Description generation batch_69f0bd40108c8190863a60cf01cc7201 completed April 28, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_69f0ef7e9f388190b33f6c16abadfde9 completed April 28, 2026, 5:33 p.m.
Created at: April 8, 2026, 9:42 p.m.