Triple
T19117049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimpo Goldline |
E467932
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Pungmu station
Pungmu station is a metro station on the Gimpo Goldline serving the city of Gimpo in Gyeonggi Province, South Korea.
|
E1392790
|
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: Pungmu station | Statement: [Gimpo Goldline, hasStation, Pungmu station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pungmu station Context triple: [Gimpo Goldline, hasStation, Pungmu station]
-
A.
Dongsu Station
Dongsu Station is a major subway station in Incheon, South Korea, serving as an important transit hub within the city's metro network.
-
B.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
C.
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
D.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
E.
Miryang Station
Miryang Station is a major railway station in Miryang, South Korea, serving as an important junction on the country’s rail 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: Pungmu station Triple: [Gimpo Goldline, hasStation, Pungmu station]
Generated description
Pungmu station is a metro station on the Gimpo Goldline serving the city of Gimpo in Gyeonggi Province, South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pungmu station Target entity description: Pungmu station is a metro station on the Gimpo Goldline serving the city of Gimpo in Gyeonggi Province, South Korea.
-
A.
Dongsu Station
Dongsu Station is a major subway station in Incheon, South Korea, serving as an important transit hub within the city's metro network.
-
B.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
C.
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
D.
Sangmu Station
Sangmu Station is a subway station on the Gwangju Metro system in Gwangju, South Korea, serving the Sangmu district.
-
E.
Miryang Station
Miryang Station is a major railway station in Miryang, South Korea, serving as an important junction on the country’s rail 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_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_6a07b4d641b48190ba517e5f9e00434b |
completed | May 16, 2026, 12:05 a.m. |
| NEDg | Description generation | batch_6a07b5a83f708190a317715bc650491b |
completed | May 16, 2026, 12:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07b67964b481909af269c6b5db6527 |
completed | May 16, 2026, 12:12 a.m. |
Created at: April 10, 2026, 12:05 p.m.