Triple
T10567352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pusanjin-gu |
E249383
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object | Bujeon Station |
E776481
|
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: Bujeon Station | Statement: [Pusanjin-gu, hasRailwayStation, Bujeon Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bujeon Station Context triple: [Pusanjin-gu, hasRailwayStation, Bujeon Station]
-
A.
Bujeon Station
chosen
Bujeon Station is a railway station in Busan, South Korea, serving as a local transportation hub with connections to regional and urban rail services.
-
B.
Bupyeong station
Bupyeong station is a major transit hub in Incheon, South Korea, serving both the Incheon Subway and Seoul Metropolitan Subway Line 1 and connecting to nearby commercial and residential areas.
-
C.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
D.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
E.
Jinju Station
Jinju Station is a railway station in Jinju, South Korea, serving as a regional transportation hub connecting the city to other parts of the country.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ef5848190b76d671ea2d26314 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e6e28a481909a90059e6ce51f6d |
completed | April 10, 2026, 8:32 p.m. |
Created at: April 6, 2026, 12:36 p.m.