Triple
T7206929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Incheon Subway |
E148687
|
entity |
| Predicate | ticketingSystem |
P3383
|
FINISHED |
| Object | Cashbee |
E467237
|
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: Cashbee | Statement: [Incheon Subway, ticketingSystem, Cashbee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cashbee Context triple: [Incheon Subway, ticketingSystem, Cashbee]
-
A.
Cashbee card
chosen
The Cashbee card is a rechargeable contactless smart card widely used in South Korea for paying public transportation fares and small retail purchases.
-
B.
DreamPay
DreamPay is a digital payments and financial services brand associated with Indian fantasy sports company Dream Sports.
-
C.
WePay
WePay is an online payment services company that provides integrated payment processing solutions for platforms, marketplaces, and software providers.
-
D.
Rosaire Paiement
Rosaire Paiement is a former Canadian professional ice hockey forward who played in the NHL during the 1960s and 1970s, notably for teams such as the Philadelphia Flyers and Vancouver Canucks.
-
E.
GrabPay
GrabPay is Grab’s digital wallet and mobile payment service used for cashless transactions across transport, food delivery, and everyday purchases in Southeast Asia.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e969c5fc819096bc03bfba12d0cf |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfc0ac008190b3ea46b4e5f13287 |
completed | March 28, 2026, 11:47 a.m. |
Created at: March 27, 2026, 2:52 p.m.