Triple
T7261153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bupyeong District |
E159653
|
entity |
| Predicate | hasMajorStation |
P1071
|
FINISHED |
| Object | Bupyeong Station |
E657906
|
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: Bupyeong Station | Statement: [Bupyeong District, hasMajorStation, Bupyeong Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bupyeong Station Context triple: [Bupyeong District, hasMajorStation, Bupyeong Station]
-
A.
Bupyeong station
chosen
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.
-
B.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
C.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
D.
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
-
E.
Oncheonjang Station
Oncheonjang Station is a subway station in Busan, South Korea, serving the Oncheonjang area in Dongnae District and providing access to its hot spring and commercial zones.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac79fd081909274aa10ffb192aa |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845df01dc8190ac219c0bb87bd83c |
completed | March 28, 2026, 9:19 p.m. |
Created at: March 27, 2026, 2:57 p.m.