Triple
T19167656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 3 (Seoul Metropolitan Subway) |
E469227
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Maebong station
Maebong station is a subway station in Seoul, South Korea, serving passengers on the city's extensive metropolitan rail network.
|
E1481777
|
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: Maebong station | Statement: [Line 3 (Seoul Metropolitan Subway), hasStation, Maebong station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maebong station Context triple: [Line 3 (Seoul Metropolitan Subway), hasStation, Maebong station]
-
A.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
B.
Bongcheon Station
Bongcheon Station is a subway station on Seoul Subway Line 2 serving the Bongcheon-dong area in Seoul, South Korea.
-
C.
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
D.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
E.
Jinju Station
Jinju Station is a railway station in Jinju, South Korea, serving as a regional transportation hub connecting the city to other parts of the country.
- 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: Maebong station Triple: [Line 3 (Seoul Metropolitan Subway), hasStation, Maebong station]
Generated description
Maebong station is a subway station in Seoul, South Korea, serving passengers on the city's extensive metropolitan rail network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maebong station Target entity description: Maebong station is a subway station in Seoul, South Korea, serving passengers on the city's extensive metropolitan rail network.
-
A.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
B.
Bongcheon Station
Bongcheon Station is a subway station on Seoul Subway Line 2 serving the Bongcheon-dong area in Seoul, South Korea.
-
C.
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
D.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
E.
Jinju Station
Jinju Station is a railway station in Jinju, South Korea, serving as a regional transportation hub connecting the city to other parts of the country.
- 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_6a09bb2efdc481908984821f8884e040 |
completed | May 17, 2026, 12:57 p.m. |
| NEDg | Description generation | batch_6a09bea2b9788190b41d3da0b5f3329e |
completed | May 17, 2026, 1:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09bf3466848190b2a5793f5f51efd7 |
completed | May 17, 2026, 1:14 p.m. |
Created at: April 10, 2026, 12:06 p.m.