Triple

T16015071
Position Surface form Disambiguated ID Type / Status
Subject CityFerry E388443 entity
Predicate fareMedium P1303 FINISHED
Object go card E872510 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: go card | Statement: [CityFerry, fareMedium, go card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: go card
Context triple: [CityFerry, fareMedium, go card]
  • A. go card chosen
    The go card is a rechargeable smartcard used for electronic ticketing on public transport services across Brisbane and the wider South East Queensland region.
  • B. 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.
  • C. ConnectCard
    ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh area.
  • D. Card Gym
    Card Gym is an athletic facility on Duke University's West Campus used primarily for physical education, recreation, and sports activities.
  • E. Go CT Card
    Go CT Card is a contactless smart fare card used for paying bus and transit fares across the CTtransit public transportation network in Connecticut.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18293ec1081909248e366967850c0 completed April 17, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbcdf2548190999a6d093c7fb64a completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:55 a.m.