Triple
T19167655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 3 (Seoul Metropolitan Subway) |
E469227
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Yangjae station |
—
|
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: Yangjae station | Statement: [Line 3 (Seoul Metropolitan Subway), hasStation, Yangjae station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yangjae station Context triple: [Line 3 (Seoul Metropolitan Subway), hasStation, Yangjae station]
-
A.
Yangjae Station
chosen
Yangjae Station is a major subway station in southern Seoul, South Korea, serving as an important transit hub on multiple lines within the city’s metro network.
-
B.
Yeongjong Station
Yeongjong Station is a railway station in Incheon, South Korea, serving the Airport Railroad Express (AREX) line that connects central Seoul with Incheon International Airport.
-
C.
Juyeop station
Juyeop station is a subway station in Goyang, South Korea, serving commuters on Seoul Subway Line 3.
-
D.
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
-
E.
Yangchon station
Yangchon station is a subway station in Gimpo, South Korea, serving as one end of the Gimpo Goldline.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f16132e081908c6b8d576163316e |
completed | April 20, 2026, 9:26 a.m. |
Created at: April 10, 2026, 12:06 p.m.