Triple

T22751689
Position Surface form Disambiguated ID Type / Status
Subject Chamberí E562716 entity
Predicate hasNotableBuilding P1544 FINISHED
Object Andén 0 – Estación de Chamberí NE NERFINISHED

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: Andén 0 – Estación de Chamberí | Statement: [Chamberí, hasNotableBuilding, Andén 0 – Estación de Chamberí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andén 0 – Estación de Chamberí
Context triple: [Chamberí, hasNotableBuilding, Andén 0 – Estación de Chamberí]
  • A. Andén 0 – Estación de Chamberí chosen
    Andén 0 – Estación de Chamberí is a former Madrid Metro station preserved as a museum, showcasing early 20th-century subway architecture, signage, and history.
  • B. Moscavide station
    Moscavide station is a Lisbon Metro stop on the Red Line serving the Moscavide area near Parque das Nações and Lisbon’s eastern transport links.
  • C. Bellas Artes station
    Bellas Artes station is a Santiago Metro station in Chile located near the National Museum of Fine Arts and the historic center of the city.
  • D. Entrecampos station
    Entrecampos station is a major railway hub in Lisbon, Portugal, serving suburban, regional, and cross-Tagus commuter services.
  • E. Olímpica station
    Olímpica station is a stop on Mexico City’s Metrobús Line B, serving passengers in the eastern part of the metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24551ec7881909a9c924dbea155f6 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f179b9ac348190bff4dc470931f7e3 completed April 29, 2026, 3:23 a.m.
Created at: April 17, 2026, 3:24 p.m.