Triple

T22515555
Position Surface form Disambiguated ID Type / Status
Subject Red de San Luis square E556636 entity
Predicate nearMetroStation P33877 FINISHED
Object Gran Vía station 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: Gran Vía station | Statement: [Red de San Luis square, nearMetroStation, Gran Vía station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gran Vía station
Context triple: [Red de San Luis square, nearMetroStation, Gran Vía station]
  • A. Lo Prado station
    Lo Prado station is an underground stop on Santiago, Chile’s Metro system serving the Lo Prado commune along Line 5.
  • B. Gran Vía metro station chosen
    Gran Vía metro station is a major Madrid Metro station in the city center, serving as an important interchange point near the Gran Vía thoroughfare.
  • C. Plaza Aragón station
    Plaza Aragón station is a stop on Mexico City Metro’s Line B serving the Plaza Aragón area in the northeastern part of the metropolitan zone.
  • D. Martínez Nadal station
    Martínez Nadal station is a rapid transit stop on the Tren Urbano system serving the San Juan metropolitan area in Puerto Rico.
  • E. Les Corts station
    Les Corts station is an underground Barcelona Metro stop in the Les Corts district, providing urban rail service on the city's Line 3.
  • 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_69e11e5657e881909f16ca58352c50da completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15e2cfc908190b3489228a1997f45 completed April 29, 2026, 1:26 a.m.
Created at: April 16, 2026, 8:50 p.m.