Triple
T19167713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 5 (Seoul Metropolitan Subway) |
E469228
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Wangsimni station
Wangsimni station is a major Seoul subway interchange and commercial hub connecting multiple metro lines and serving the Seongdong District.
|
E1490038
|
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: Wangsimni station | Statement: [Line 5 (Seoul Metropolitan Subway), hasStation, Wangsimni station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wangsimni station Context triple: [Line 5 (Seoul Metropolitan Subway), hasStation, Wangsimni station]
-
A.
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
B.
Hwanggumbol Station
Hwanggumbol Station is a stop on the Pyongyang Metro system in North Korea, serving passengers on one of the capital’s underground lines.
-
C.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
D.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
E.
Bulgwang Station
Bulgwang Station is a subway station in Seoul, South Korea, serving as an interchange stop on the city's 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: Wangsimni station Triple: [Line 5 (Seoul Metropolitan Subway), hasStation, Wangsimni station]
Generated description
Wangsimni station is a major Seoul subway interchange and commercial hub connecting multiple metro lines and serving the Seongdong District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wangsimni station Target entity description: Wangsimni station is a major Seoul subway interchange and commercial hub connecting multiple metro lines and serving the Seongdong District.
-
A.
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
B.
Hwanggumbol Station
Hwanggumbol Station is a stop on the Pyongyang Metro system in North Korea, serving passengers on one of the capital’s underground lines.
-
C.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
D.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
E.
Bulgwang Station
Bulgwang Station is a subway station in Seoul, South Korea, serving as an interchange stop on the city's 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f16132e081908c6b8d576163316e |
completed | April 20, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09eec4ce9c8190b76efb4d6f038125 |
completed | May 17, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a09efc6a57c81908c72e794c16989d4 |
completed | May 17, 2026, 4:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09f07a090c8190aead09c3b06e0e34 |
completed | May 17, 2026, 4:44 p.m. |
Created at: April 10, 2026, 12:06 p.m.