Triple

T596323
Position Surface form Disambiguated ID Type / Status
Subject Davis station E17390 entity
Predicate fareSystem P395 FINISHED
Object CharlieTicket E16692 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: CharlieTicket | Statement: [Davis station, fareSystem, CharlieTicket]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CharlieTicket
Context triple: [Davis station, fareSystem, CharlieTicket]
  • A. CharlieTicket chosen
    CharlieTicket is a reusable paper smart card used for paying fares on Boston’s MBTA public transit system.
  • B. CharlieCard
    The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
  • C. Transportation and Ticket Center
    The Transportation and Ticket Center is Walt Disney World's primary transit and ticketing hub, where guests park, purchase admission, and transfer via monorail or ferryboat to the Magic Kingdom and other resort areas.
  • D. CheapTickets
    CheapTickets is an online travel agency brand offering discounted flights, hotels, and vacation packages, operated under the Expedia Group portfolio.
  • E. The Big Ticket
    The Big Ticket is the famous nickname of NBA Hall of Famer Kevin Garnett, known for his intense competitiveness and all-around dominance on the basketball court.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bd3e5e08190be95cb2009aad42d completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c766508190ae39b6e254a07bc3 completed March 2, 2026, 4:57 a.m.
Created at: March 1, 2026, 7:33 p.m.