Triple
T17122934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ansan |
E415511
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object |
Sangnoksu Station
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
|
E1255773
|
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: Sangnoksu Station | Statement: [Ansan, hasRailwayStation, Sangnoksu Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sangnoksu Station Context triple: [Ansan, hasRailwayStation, Sangnoksu 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.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
D.
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.
-
E.
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
- 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: Sangnoksu Station Triple: [Ansan, hasRailwayStation, Sangnoksu Station]
Generated description
Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sangnoksu Station Target entity description: Sangnoksu Station is a subway station in Ansan, South Korea, serving as part of the Seoul Metropolitan Subway network.
-
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.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
D.
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.
-
E.
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e80ac2cc819084fab829917c950a |
completed | April 18, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fbff4b48190970073eb3b9d5d75 |
completed | May 11, 2026, 4:49 a.m. |
| NEDg | Description generation | batch_6a01606f478c81908de90300e89200ab |
completed | May 11, 2026, 4:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a016101ad308190b60633cb65f8e3e1 |
completed | May 11, 2026, 4:54 a.m. |
Created at: April 10, 2026, 5:36 a.m.