Triple

T12314017
Position Surface form Disambiguated ID Type / Status
Subject Line 7-Rubi E293551 entity
Predicate hasStation P35 FINISHED
Object Barra Funda station
Barra Funda station is a major intermodal rail and metro hub in São Paulo, Brazil, serving suburban, regional, and urban transit lines.
 E998726 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: Barra Funda station | Statement: [Line 7-Rubi, hasStation, Barra Funda station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Barra Funda station
Context triple: [Line 7-Rubi, hasStation, Barra Funda station]
  • A. Campo Belo station
    Campo Belo station is an underground metro station in São Paulo, Brazil, serving the city’s Line 5–Lilac.
  • B. Adolfo Pinheiro station
    Adolfo Pinheiro station is an underground metro station in São Paulo, Brazil, serving passengers on Line 5–Lilac of the São Paulo Metro system.
  • C. San Pablo station
    San Pablo station is an interchange station in the Santiago Metro network that connects Line 5 with other lines in the western part of Santiago, Chile.
  • D. Capão Redondo station
    Capão Redondo station is a metro terminus in São Paulo, Brazil, serving the southern region of the city on Line 5–Lilac.
  • E. Río de Janeiro station
    Río de Janeiro station is a stop on Line A of the Buenos Aires Underground, serving passengers in the Caballito neighborhood of Argentina’s capital.
  • 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: Barra Funda station
Triple: [Line 7-Rubi, hasStation, Barra Funda station]
Generated description
Barra Funda station is a major intermodal rail and metro hub in São Paulo, Brazil, serving suburban, regional, and urban transit lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Barra Funda station
Target entity description: Barra Funda station is a major intermodal rail and metro hub in São Paulo, Brazil, serving suburban, regional, and urban transit lines.
  • A. Campo Belo station
    Campo Belo station is an underground metro station in São Paulo, Brazil, serving the city’s Line 5–Lilac.
  • B. Adolfo Pinheiro station
    Adolfo Pinheiro station is an underground metro station in São Paulo, Brazil, serving passengers on Line 5–Lilac of the São Paulo Metro system.
  • C. San Pablo station
    San Pablo station is an interchange station in the Santiago Metro network that connects Line 5 with other lines in the western part of Santiago, Chile.
  • D. Capão Redondo station
    Capão Redondo station is a metro terminus in São Paulo, Brazil, serving the southern region of the city on Line 5–Lilac.
  • E. Río de Janeiro station
    Río de Janeiro station is a stop on Line A of the Buenos Aires Underground, serving passengers in the Caballito neighborhood of Argentina’s capital.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f03d3c88190baedffb83465bff8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671837a5c81908a7f41ac7e2bef59 completed May 2, 2026, 9:49 p.m.
NEDg Description generation batch_69f6749c2ddc8190945270e6e5b210dd completed May 2, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69f675c42fec8190b60751c0db88f3b6 completed May 2, 2026, 10:08 p.m.
Created at: April 8, 2026, 9:53 p.m.