Triple
T6570333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeonsu District |
E155416
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Yeonsu Station
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
|
E615538
|
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: Yeonsu Station | Statement: [Yeonsu District, hasStation, Yeonsu Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeonsu Station Context triple: [Yeonsu District, hasStation, Yeonsu Station]
-
A.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
B.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
C.
Yangjae Station
Yangjae Station is a major subway station in southern Seoul, South Korea, serving as an important transit hub on multiple lines within the city’s metro network.
-
D.
Oncheonjang Station
Oncheonjang Station is a subway station in Busan, South Korea, serving the Oncheonjang area in Dongnae District and providing access to its hot spring and commercial zones.
-
E.
Kwangbok Station
Kwangbok Station is a stop on the Pyongyang Metro system in North Korea, serving passengers along one of the capital’s main underground transit lines.
- 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: Yeonsu Station Triple: [Yeonsu District, hasStation, Yeonsu Station]
Generated description
Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yeonsu Station Target entity description: Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
-
A.
Myeongnyun Station
Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
-
B.
Kwangmyong Station
Kwangmyong Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
C.
Yangjae Station
Yangjae Station is a major subway station in southern Seoul, South Korea, serving as an important transit hub on multiple lines within the city’s metro network.
-
D.
Oncheonjang Station
Oncheonjang Station is a subway station in Busan, South Korea, serving the Oncheonjang area in Dongnae District and providing access to its hot spring and commercial zones.
-
E.
Kwangbok Station
Kwangbok Station is a stop on the Pyongyang Metro system in North Korea, serving passengers along one of the capital’s main underground transit lines.
- 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_69c688151254819080387f87deab8fa7 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae5791e881909d0b340aa63c6223 |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70ae438b0819086449c169e5c7e49 |
completed | March 27, 2026, 10:55 p.m. |
| NEDg | Description generation | batch_69c70be7d9308190b7e4e36e89c12773 |
completed | March 27, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c70c618a2c819097e0cfd869bf99b7 |
completed | March 27, 2026, 11:01 p.m. |
Created at: March 27, 2026, 1:53 p.m.