Triple

T7548758
Position Surface form Disambiguated ID Type / Status
Subject Metrolinx E178473 entity
Predicate responsibleFor P636 FINISHED
Object PRESTO fare card system E31472 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: PRESTO fare card system | Statement: [Metrolinx, responsibleFor, PRESTO fare card system]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PRESTO fare card system
Context triple: [Metrolinx, responsibleFor, PRESTO fare card system]
  • A. Presto card chosen
    The Presto card is a reloadable smart card used for paying public transit fares across the Greater Toronto and Hamilton Area and other regions in Ontario, Canada.
  • B. Pronto card
    The Pronto card is a reloadable smart fare card used for paying public transit fares across the San Diego Metropolitan Transit System and related services.
  • C. Clipper card
    The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
  • D. TAP card
    The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
  • E. OPUS card
    The OPUS card is a reusable, contactless smart card used for public transit fare payment across the greater Montreal area and other regions in Quebec.
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f89b9afc8190b3e61a8e2cea7ad7 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f2b0de48190a854b4d4935c2254 completed March 28, 2026, 9:59 p.m.
Created at: March 27, 2026, 3:49 p.m.