Triple

T22808520
Position Surface form Disambiguated ID Type / Status
Subject MBTA bus route 9 E564603 entity
Predicate usesTicketing P5937 FINISHED
Object CharlieCard NE NERFINISHED

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 bus route 9, usesTicketing, CharlieCard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CharlieCard
Context triple: [MBTA bus route 9, usesTicketing, CharlieCard]
  • A. CharlieCard chosen
    The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
  • B. ConnectCard
    ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh area.
  • C. 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.
  • D. Clubcard
    Clubcard is Tesco’s customer loyalty program that offers members points, discounts, and personalized offers on their shopping.
  • E. Credo Card
    Credo Card is a core service philosophy tool used by The Ritz-Carlton Hotel Company to communicate and reinforce its brand standards, values, and commitment to exceptional guest service among employees.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245823f4c8190ade442cdcc2c224a completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17d5e0b088190ad0b9cc0d5aa1d96 completed April 29, 2026, 3:39 a.m.
Created at: April 17, 2026, 3:32 p.m.