Triple

T11893664
Position Surface form Disambiguated ID Type / Status
Subject Autódromo José Carlos Pace E282980 entity
Predicate corner P7149 FINISHED
Object Juncão
Juncão is a famous late-circuit corner at Brazil’s Interlagos racetrack that leads onto the main uphill straight and is crucial for lap times and overtaking opportunities.
E954272 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: Juncão | Statement: [Autódromo José Carlos Pace, corner, Juncão]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juncão
Context triple: [Autódromo José Carlos Pace, corner, Juncão]
  • A. Itapemirim
    Itapemirim is a coastal municipality in southeastern Brazil known for its beaches, fishing activities, and location within the state of Espírito Santo.
  • B. Ribeirinha
    Ribeirinha is a civil parish located within the municipality of Angra do Heroísmo on Terceira Island in the Azores, Portugal.
  • C. Ribeirinha
    Ribeirinha is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • D. Jordão
    Jordão is a neighborhood of Recife, Brazil, known as a largely residential area on the city’s outskirts.
  • E. Pirapora
    Pirapora is a municipality in the state of Minas Gerais, Brazil, known for its location on the São Francisco River and its river-based tourism and commerce.
  • 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: Juncão
Triple: [Autódromo José Carlos Pace, corner, Juncão]
Generated description
Juncão is a famous late-circuit corner at Brazil’s Interlagos racetrack that leads onto the main uphill straight and is crucial for lap times and overtaking opportunities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Juncão
Target entity description: Juncão is a famous late-circuit corner at Brazil’s Interlagos racetrack that leads onto the main uphill straight and is crucial for lap times and overtaking opportunities.
  • A. Itapemirim
    Itapemirim is a coastal municipality in southeastern Brazil known for its beaches, fishing activities, and location within the state of Espírito Santo.
  • B. Ribeirinha
    Ribeirinha is a civil parish located on Faial Island in the Azores archipelago of Portugal.
  • C. Ribeirinha
    Ribeirinha is a civil parish located within the municipality of Angra do Heroísmo on Terceira Island in the Azores, Portugal.
  • D. Jordão
    Jordão is a neighborhood of Recife, Brazil, known as a largely residential area on the city’s outskirts.
  • E. Pirapora
    Pirapora is a municipality in the state of Minas Gerais, Brazil, known for its location on the São Francisco River and its river-based tourism and commerce.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1172988190a2c13d37220f2f93 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43fe43c7c8190a85d464fd48e00d9 completed May 1, 2026, 5:53 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, 9:44 p.m.