Triple

T2720390
Position Surface form Disambiguated ID Type / Status
Subject State of São Paulo E60066 entity
Predicate hasCity P316 FINISHED
Object Ourinhos
Ourinhos is a municipality in the southwestern part of the state of São Paulo, Brazil, known as a regional commercial and agricultural center.
E294683 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: Ourinhos | Statement: [State of São Paulo, hasCity, Ourinhos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ourinhos
Context triple: [State of São Paulo, hasCity, Ourinhos]
  • A. Afogados
    Afogados is a populous neighborhood in the Brazilian city of Recife, known for its busy commercial areas and dense urban character.
  • B. Dois Unidos
    Dois Unidos is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
  • C. Icó
    Icó is a historic municipality in northeastern Brazil known for its colonial architecture and cultural heritage within the state of Ceará.
  • D. Igarassu
    Igarassu is one of Brazil’s oldest colonial towns, known for its historic churches and coastal location in the northeastern state of Pernambuco.
  • E. Parnamirim
    Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
  • 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: Ourinhos
Triple: [State of São Paulo, hasCity, Ourinhos]
Generated description
Ourinhos is a municipality in the southwestern part of the state of São Paulo, Brazil, known as a regional commercial and agricultural center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ourinhos
Target entity description: Ourinhos is a municipality in the southwestern part of the state of São Paulo, Brazil, known as a regional commercial and agricultural center.
  • A. Afogados
    Afogados is a populous neighborhood in the Brazilian city of Recife, known for its busy commercial areas and dense urban character.
  • B. Dois Unidos
    Dois Unidos is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
  • C. Icó
    Icó is a historic municipality in northeastern Brazil known for its colonial architecture and cultural heritage within the state of Ceará.
  • D. Igarassu
    Igarassu is one of Brazil’s oldest colonial towns, known for its historic churches and coastal location in the northeastern state of Pernambuco.
  • E. Parnamirim
    Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdab06d388190acf690787fe58ab5 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbc05d148190b6a0faf10443519d completed March 10, 2026, 6:35 a.m.
NEDg Description generation batch_69afbc8415388190a39d459ff7a411e4 completed March 10, 2026, 6:39 a.m.
NED2 Entity disambiguation (via description) batch_69afbcc460b88190986844c39165ef14 completed March 10, 2026, 6:40 a.m.
Created at: March 6, 2026, 9:55 p.m.