Triple
T14824682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton railway station |
E348539
|
entity |
| Predicate | hasTicketingSystem |
P3383
|
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: [Milton railway station, hasTicketingSystem, go card]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: go card Context triple: [Milton railway station, hasTicketingSystem, 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe7a8dc8190bcb5ecfa1cbf1601 |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe389d7c848190813be06bed7813d7 |
completed | May 8, 2026, 7:25 p.m. |
Created at: April 10, 2026, 1:51 a.m.