Triple

T10574704
Position Surface form Disambiguated ID Type / Status
Subject Line 1 (Barcelona Metro) E249578 entity
Predicate hasStation P35 FINISHED
Object Torrassa station E599008 NE FINISHED

How this triple was built (2 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: [Line 1 (Barcelona Metro), hasStation, Torrassa station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torrassa station
Context triple: [Line 1 (Barcelona Metro), hasStation, Torrassa station]
  • A. Torrassa station chosen
    Torrassa station is an underground rapid transit stop in L'Hospitalet de Llobregat that forms part of Barcelona’s metro network.
  • B. Toberín station
    Toberín station is a public transit stop in Bogotá’s TransMilenio bus rapid transit system serving the Toberín neighborhood and surrounding areas.
  • C. Impulsora station
    Impulsora station is a Mexico City Metro station serving the northeastern area of the metropolitan zone on Line B.
  • D. 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.
  • E. Aventura station
    Aventura station is a Brightline intercity rail station in Aventura, Florida, serving as a stop on the higher-speed passenger rail line connecting Miami and Orlando.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d52749dda08190b0c9627a931c5848 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b5d89748190bb398943e4a16e9b completed April 10, 2026, 7:11 p.m.
Created at: April 6, 2026, 12:38 p.m.