Triple
T17811913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheongju |
E444728
|
entity |
| Predicate | hasTransport |
P1298
|
FINISHED |
| Object |
Osong Station
Osong Station is a major railway hub in South Korea that serves high-speed KTX trains and connects multiple key rail lines.
|
E1290842
|
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: Osong Station | Statement: [Cheongju, hasTransport, Osong Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osong Station Context triple: [Cheongju, hasTransport, Osong Station]
-
A.
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.
-
B.
Jonggak Station
Jonggak Station is a major Seoul Metropolitan Subway station in central Seoul, South Korea, serving the bustling Jongno business and shopping district.
-
C.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
D.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
E.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
- 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: Osong Station Triple: [Cheongju, hasTransport, Osong Station]
Generated description
Osong Station is a major railway hub in South Korea that serves high-speed KTX trains and connects multiple key rail lines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Osong Station Target entity description: Osong Station is a major railway hub in South Korea that serves high-speed KTX trains and connects multiple key rail lines.
-
A.
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.
-
B.
Jonggak Station
Jonggak Station is a major Seoul Metropolitan Subway station in central Seoul, South Korea, serving the bustling Jongno business and shopping district.
-
C.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
D.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
E.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887b5e50819098506f0b92d709b5 |
completed | April 19, 2026, 7:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0306eda2bc8190909739e01af1b9ad |
completed | May 12, 2026, 10:54 a.m. |
| NEDg | Description generation | batch_6a0307bd9d2c8190a55e726180c8c547 |
completed | May 12, 2026, 10:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03080d46fc8190890000cfd0ede60e |
completed | May 12, 2026, 10:59 a.m. |
Created at: April 10, 2026, 10:14 a.m.