Triple
T19734375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeongui–Jungang Line |
E473938
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Munsan Station
Munsan Station is a railway station in Paju, South Korea, serving as a key northern stop near the Demilitarized Zone on the Gyeongui–Jungang Line.
|
E1556155
|
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: Munsan Station | Statement: [Gyeongui–Jungang Line, terminus, Munsan Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Munsan Station Context triple: [Gyeongui–Jungang Line, terminus, Munsan Station]
-
A.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
B.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
C.
Bonghwasan Station
Bonghwasan Station is a subway station in Seoul, South Korea, serving as the northeastern terminus of Seoul Subway Line 6.
-
D.
Sangwolgok Station
Sangwolgok Station is a subway station on Seoul’s Line 6 serving the Sangwolgok neighborhood in Seongbuk-gu, South Korea.
-
E.
Unseo Station
Unseo Station is a railway station in Incheon, South Korea, serving the Airport Railroad Express (AREX) line that connects central Seoul with Incheon International Airport.
- 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: Munsan Station Triple: [Gyeongui–Jungang Line, terminus, Munsan Station]
Generated description
Munsan Station is a railway station in Paju, South Korea, serving as a key northern stop near the Demilitarized Zone on the Gyeongui–Jungang Line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Munsan Station Target entity description: Munsan Station is a railway station in Paju, South Korea, serving as a key northern stop near the Demilitarized Zone on the Gyeongui–Jungang Line.
-
A.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
B.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
C.
Bonghwasan Station
Bonghwasan Station is a subway station in Seoul, South Korea, serving as the northeastern terminus of Seoul Subway Line 6.
-
D.
Sangwolgok Station
Sangwolgok Station is a subway station on Seoul’s Line 6 serving the Sangwolgok neighborhood in Seongbuk-gu, South Korea.
-
E.
Unseo Station
Unseo Station is a railway station in Incheon, South Korea, serving the Airport Railroad Express (AREX) line that connects central Seoul with Incheon International Airport.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515b4d308190af3be1787fa7c65b |
completed | April 20, 2026, 4:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ba78fd40081909715cd27cf05236a |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0ba7fee49481909915675cd5b21df2 |
completed | May 18, 2026, 11:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba8ac6b008190bf0441b47af7d93b |
completed | May 19, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:47 p.m.