Triple

T7076006
Position Surface form Disambiguated ID Type / Status
Subject Madrid Metro Line 1 E164819 entity
Predicate hasStation P35 FINISHED
Object Valdecarros E639931 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: Valdecarros | Statement: [Madrid Metro Line 1, hasStation, Valdecarros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valdecarros
Context triple: [Madrid Metro Line 1, hasStation, Valdecarros]
  • A. Valdecarros chosen
    Valdecarros is a Madrid Metro station serving as the southeastern terminus of Line 1 in the Valdecarros neighborhood of the city.
  • B. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • C. Requena
    Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
  • D. Valdemaqueda
    Valdemaqueda is a small municipality in the Community of Madrid, Spain, known for its rural landscape and proximity to the Sierra de Guadarrama.
  • E. Carso
    Carso is a limestone plateau region in northeastern Italy and southwestern Slovenia, known for its distinctive karst landscapes, caves, and sinkholes.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4ebf4048190bf5d7156817f93a7 completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a31a43b481908e535afc393b242a completed March 28, 2026, 9:44 a.m.
Created at: March 27, 2026, 2:40 p.m.