Triple

T10695157
Position Surface form Disambiguated ID Type / Status
Subject Catedral station E252116 entity
Predicate fareSystem P395 FINISHED
Object SUBE E191067 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: SUBE | Statement: [Catedral station, fareSystem, SUBE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SUBE
Context triple: [Catedral station, fareSystem, SUBE]
  • A. SUBE card chosen
    The SUBE card is a rechargeable contactless smart card used as an integrated electronic payment system for public transportation across Buenos Aires and other parts of Argentina.
  • B. Subte
    Subte is the rapid transit metro system serving Buenos Aires, Argentina, and one of the oldest underground rail networks in Latin America.
  • C. Transantiago
    Transantiago was the former name of Santiago, Chile’s integrated public transportation system, encompassing its bus and metro networks.
  • D. Buenos Aires Premetro
    Buenos Aires Premetro is a light rail feeder system in Buenos Aires that connects outlying neighborhoods to the city’s main subway network.
  • E. Metrobús Buenos Aires
    Metrobús Buenos Aires is a bus rapid transit (BRT) system in Buenos Aires that uses dedicated lanes and priority measures to improve the speed and reliability of urban bus services.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd39c3788190bb7cd0acf8b6efdd completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998da1738819099a9090c3e8badc9 completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:11 p.m.