Triple

T141763
Position Surface form Disambiguated ID Type / Status
Subject MBTA E2866 entity
Predicate fareSystem P395 FINISHED
Object CharlieCard E3327 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: CharlieCard | Statement: [MBTA, fareSystem, CharlieCard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CharlieCard
Context triple: [MBTA, fareSystem, CharlieCard]
  • A. CharlieCard chosen
    The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
  • B. 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.
  • C. SmarTrip
    SmarTrip is a rechargeable contactless smart card used to pay fares on the Washington, D.C. region’s public transit systems.
  • D. MetroCard
    MetroCard is a magnetic stripe payment card formerly used as the primary method for paying fares on New York City’s public transit system, including subways and buses.
  • E. SEPTA Key
    SEPTA Key is a contactless smart fare card and payment system used across Philadelphia’s SEPTA public transit network.
  • 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_69a2521e35c08190b28e5c9f1e3c9b59 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a257c9cab8819095e8d9fa32c1fbc6 completed Feb. 28, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2b85fe4d481909e39b745857b62e7 completed Feb. 28, 2026, 9:41 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.