Triple

T2810011
Position Surface form Disambiguated ID Type / Status
Subject Kendall/MIT station E54144 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: [Kendall/MIT station, fareSystem, CharlieCard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CharlieCard
Context triple: [Kendall/MIT station, 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. CharmCard
    CharmCard is a contactless smart fare card used for paying transit fares across the Maryland Transit Administration’s bus, rail, and other public transportation services.
  • C. Card
    Card is a surname most notably borne by Andrew Card, a former White House Chief of Staff under U.S. President George W. Bush.
  • D. Go-To Card
    The Go-To Card is a reusable, contactless smart card used to pay fares on the Minneapolis–Saint Paul METRO transit system.
  • E. 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.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde335b38819090c70d5e2ca14d79 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce97c3008190a966441d719d1d1c completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.