Triple
T19117243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 6 |
E467936
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Cheonggu Station
Cheonggu Station is a subway station on Seoul’s extensive metropolitan rail network, serving passengers on Line 6.
|
E1445612
|
NE FINISHED |
How this triple was built (4 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: Cheonggu Station | Statement: [Line 6, hasStation, Cheonggu Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheonggu Station Context triple: [Line 6, hasStation, Cheonggu Station]
-
A.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
B.
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
-
C.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
D.
Gwangmyeong Station
Gwangmyeong Station is a major high-speed rail station in Gwangmyeong, South Korea, serving as an important stop on the KTX network connecting Seoul with other key cities nationwide.
-
E.
Hapjeong Station
Hapjeong Station is a major Seoul Metropolitan Subway interchange station in Mapo-gu, connecting Line 2 and Line 6 near the Hongdae and Mangwon neighborhoods.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cheonggu Station Triple: [Line 6, hasStation, Cheonggu Station]
Generated description
Cheonggu Station is a subway station on Seoul’s extensive metropolitan rail network, serving passengers on Line 6.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cheonggu Station Target entity description: Cheonggu Station is a subway station on Seoul’s extensive metropolitan rail network, serving passengers on Line 6.
-
A.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
B.
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
-
C.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
D.
Gwangmyeong Station
Gwangmyeong Station is a major high-speed rail station in Gwangmyeong, South Korea, serving as an important stop on the KTX network connecting Seoul with other key cities nationwide.
-
E.
Hapjeong Station
Hapjeong Station is a major Seoul Metropolitan Subway interchange station in Mapo-gu, connecting Line 2 and Line 6 near the Hongdae and Mangwon neighborhoods.
- F. None of above. chosen
Provenance (5 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e399a6d8819090a9501ff1637b9d |
completed | April 20, 2026, 8:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08d7c569a481909b595b0517fbee7d |
completed | May 16, 2026, 8:47 p.m. |
| NEDg | Description generation | batch_6a08d902cab481908d0a7b28699a2031 |
completed | May 16, 2026, 8:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08d9693acc8190acc75cbbf06b62da |
completed | May 16, 2026, 8:54 p.m. |
Created at: April 10, 2026, 12:05 p.m.