Triple

T2280425
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Metro E51267 entity
Predicate nativeName P15 FINISHED
Object Metro de Barcelona E51267 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: Metro de Barcelona | Statement: [Barcelona Metro, nativeName, Metro de Barcelona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metro de Barcelona
Context triple: [Barcelona Metro, nativeName, Metro de Barcelona]
  • A. Barcelona Metro chosen
    Barcelona Metro is the rapid transit rail network serving the city of Barcelona and its metropolitan area, known for its extensive coverage and integration with other public transport modes.
  • B. Transports Metropolitans de Barcelona
    Transports Metropolitans de Barcelona is the main public transport authority in Barcelona, managing the city’s metro, bus, and other urban transit services.
  • C. Madrid Metro
    Madrid Metro is the extensive rapid transit system serving Spain’s capital, known for its large network, frequent service, and role as a primary mode of urban transportation.
  • D. Seville Metro
    Seville Metro is a rapid transit system serving the city of Seville and its metropolitan area in southern Spain.
  • E. Metro Ligero de Madrid
    Metro Ligero de Madrid is a light rail system serving several suburban and peripheral areas of Madrid, complementing the city's main metro network.
  • 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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc21ac3d48190abef254e1c3f45e8 completed March 7, 2026, 6:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae894cbb788190826b27cefb856651 completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:48 p.m.