Triple

T7702183
Position Surface form Disambiguated ID Type / Status
Subject 501 Queen E174524 entity
Predicate fareMedium P1303 FINISHED
Object Presto card 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 card | Statement: [501 Queen, fareMedium, Presto card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Presto card
Context triple: [501 Queen, fareMedium, Presto card]
  • 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. Metcard
    Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
  • D. 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.
  • E. Breeze Card
    The Breeze Card is a reusable smart fare card used for paying transit fares across the Metropolitan Atlanta Rapid Transit Authority (MARTA) system in Atlanta, Georgia.
  • 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_69c6995a72cc8190998e56daa6f8e453 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7028a2f9881908a2f1a257566fb7b completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8acbc2024819083576f5a11c1e3a8 completed March 29, 2026, 4:38 a.m.
Created at: March 27, 2026, 4:03 p.m.