Triple

T6457573
Position Surface form Disambiguated ID Type / Status
Subject Renfe Operadora E142030 entity
Predicate brand P1500 FINISHED
Object Cercanías E582703 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: Cercanías | Statement: [Renfe Operadora, brand, Cercanías]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cercanías
Context triple: [Renfe Operadora, brand, Cercanías]
  • A. Cercanías chosen
    Cercanías is Spain’s network of suburban and commuter rail services that connect major cities with their surrounding metropolitan areas.
  • B. Seville commuter rail
    Seville commuter rail is a regional rail network serving the metropolitan area of Seville, Spain, connecting the city with its surrounding suburbs and towns.
  • C. Cercanías Madrid Line C-2
    Cercanías Madrid Line C-2 is a commuter rail line in the Madrid metropolitan area that connects central Madrid with its northeastern suburbs as part of the Cercanías Madrid network.
  • D. Tren Urbano
    Tren Urbano is a rapid transit rail system serving the San Juan metropolitan area in Puerto Rico, providing urban mass transportation across key municipalities.
  • E. Tren Ligero
    Tren Ligero is a light rail transit system in Mexico City that complements the metro and bus networks by serving southern areas of the city.
  • 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_69c008d2f91c8190a8178767a35e08fc completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069d758508190b9c7358ef84f8169 completed March 22, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bdef4a881908f3d7b6eefab7def completed March 27, 2026, 9:20 a.m.
Created at: March 22, 2026, 4:48 p.m.