Triple
T20132547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwanghwamun Station |
E490930
|
entity |
| Predicate | fareCardAccepted |
P9955
|
FINISHED |
| Object | T-money |
—
|
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: T-money | Statement: [Gwanghwamun Station, fareCardAccepted, T-money]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-money Context triple: [Gwanghwamun Station, fareCardAccepted, T-money]
-
A.
T-money card
chosen
The T-money card is a rechargeable contactless smart card widely used in South Korea for convenient payment of public transportation fares and small purchases.
-
B.
T-Money
T-Money is a television personality and DJ best known for co-hosting the influential hip-hop music video show "Yo! MTV Raps."
-
C.
Naver Pay
Naver Pay is a South Korean digital payment and fintech service that enables users to make online and mobile transactions within Naver’s ecosystem and at affiliated merchants.
-
D.
Octopus card
The Octopus card is a rechargeable contactless smart card widely used in Hong Kong for public transport fares and everyday electronic payments.
-
E.
Seoul Metro
Seoul Metro is the public corporation responsible for operating a major portion of the Seoul Metropolitan Subway system in South Korea.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66763ee908190af64af31b4ca2377 |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:31 p.m.