Triple

T11795653
Position Surface form Disambiguated ID Type / Status
Subject Rondônia E280499 entity
Predicate hasCity P316 FINISHED
Object Vilhena
Vilhena is a municipality in the southern part of the Brazilian state of Rondônia, known as an important regional agricultural and commercial center.
 E954143 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: Vilhena | Statement: [Rondônia, hasCity, Vilhena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vilhena
Context triple: [Rondônia, hasCity, Vilhena]
  • A. Conceição
    Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • B. Corumbá
    Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
  • C. Baraguá
    Baraguá is a historic locality in eastern Cuba best known as the site of the 1878 Baraguá Protest, a landmark act of resistance during the Ten Years' War for Cuban independence.
  • D. Caxangá
    Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
  • E. Tanguá
    Tanguá is a small municipality in the state of Rio de Janeiro, Brazil, known for its rural character and integration into the greater Rio de Janeiro metropolitan area.
  • 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: Vilhena
Triple: [Rondônia, hasCity, Vilhena]
Generated description
Vilhena is a municipality in the southern part of the Brazilian state of Rondônia, known as an important regional agricultural and commercial center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vilhena
Target entity description: Vilhena is a municipality in the southern part of the Brazilian state of Rondônia, known as an important regional agricultural and commercial center.
  • A. Conceição
    Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • B. Corumbá
    Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
  • C. Baraguá
    Baraguá is a historic locality in eastern Cuba best known as the site of the 1878 Baraguá Protest, a landmark act of resistance during the Ten Years' War for Cuban independence.
  • D. Caxangá
    Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
  • E. Tanguá
    Tanguá is a small municipality in the state of Rio de Janeiro, Brazil, known for its rural character and integration into the greater Rio de Janeiro metropolitan area.
  • 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_69f43f8a57ec8190aded70ae89aa8cf7 completed May 1, 2026, 5:52 a.m.
NEDg Description generation batch_69f448f506a48190a0f1b89ad570fad5 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44ad185cc8190893cf663cfed6980 completed May 1, 2026, 6:40 a.m.
Created at: April 8, 2026, 9:42 p.m.