Triple

T6637192
Position Surface form Disambiguated ID Type / Status
Subject Metro line L9 Sud E150486 entity
Predicate hasStation P35 FINISHED
Object Torrassa station
Torrassa station is an underground rapid transit stop in L'Hospitalet de Llobregat that forms part of Barcelona’s metro network.
 E599008 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: Torrassa station | Statement: [Metro line L9 Sud, hasStation, Torrassa station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Torrassa station
Context triple: [Metro line L9 Sud, hasStation, Torrassa station]
  • A. Toberín station
    Toberín station is a public transit stop in Bogotá’s TransMilenio bus rapid transit system serving the Toberín neighborhood and surrounding areas.
  • B. Impulsora station
    Impulsora station is a Mexico City Metro station serving the northeastern area of the metropolitan zone on Line B.
  • C. La Granja station
    La Granja station is a stop on Madrid Metro’s Line 4A serving the La Granja area in the city’s rapid transit network.
  • D. J. Ruiz station
    J. Ruiz station is an elevated stop on Manila’s LRT Line 2 serving commuters in the San Juan area of Metro Manila, Philippines.
  • E. Barón station
    Barón station is a passenger rail stop on the Valparaíso Metro system in Valparaíso, Chile, serving the coastal urban 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: Torrassa station
Triple: [Metro line L9 Sud, hasStation, Torrassa station]
Generated description
Torrassa station is an underground rapid transit stop in L'Hospitalet de Llobregat that forms part of Barcelona’s metro network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Torrassa station
Target entity description: Torrassa station is an underground rapid transit stop in L'Hospitalet de Llobregat that forms part of Barcelona’s metro network.
  • A. Toberín station
    Toberín station is a public transit stop in Bogotá’s TransMilenio bus rapid transit system serving the Toberín neighborhood and surrounding areas.
  • B. Impulsora station
    Impulsora station is a Mexico City Metro station serving the northeastern area of the metropolitan zone on Line B.
  • C. La Granja station
    La Granja station is a stop on Madrid Metro’s Line 4A serving the La Granja area in the city’s rapid transit network.
  • D. J. Ruiz station
    J. Ruiz station is an elevated stop on Manila’s LRT Line 2 serving commuters in the San Juan area of Metro Manila, Philippines.
  • E. Barón station
    Barón station is a passenger rail stop on the Valparaíso Metro system in Valparaíso, Chile, serving the coastal urban 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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afcf439c8190b9334b34774da821 completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbf71874819080cc89b6740b1567 completed March 27, 2026, 6:27 p.m.
NEDg Description generation batch_69c6cd0bb0e48190ae51fde4b4631f65 completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cd90b9208190b4c5bf44db073314 completed March 27, 2026, 6:33 p.m.
Created at: March 27, 2026, 1:59 p.m.