Triple
T15200573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 오산시 |
E363256
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object |
오산대역
오산대역은 경기도 오산시에 위치한 수도권 전철 1호선의 역으로, 오산대학과 인근 지역을 연결하는 주요 교통 거점이다.
|
E1144210
|
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: 오산대역 | Statement: [오산시, hasRailwayStation, 오산대역]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 오산대역 Context triple: [오산시, hasRailwayStation, 오산대역]
-
A.
Gwanak Station
Gwanak Station is a railway station in South Korea that serves the city of Anyang and connects it to the broader Seoul metropolitan rail network.
-
B.
Yeongdeungpo Station
Yeongdeungpo Station is a major railway and subway interchange in Seoul, South Korea, serving as an important transportation and commercial hub for the Yeongdeungpo area.
-
C.
Hongik University Station
Hongik University Station is a major subway station in Seoul’s Mapo District, serving the popular Hongdae area known for its universities, nightlife, and arts scene.
-
D.
Suwon Station
Suwon Station is a major railway and subway hub in Suwon, South Korea, serving as a key transit, commercial, and regional transportation center.
-
E.
Seoul National University Station
Seoul National University Station is a major Seoul Metropolitan Subway stop serving the area near Seoul National University in southern Seoul.
- 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: 오산대역 Triple: [오산시, hasRailwayStation, 오산대역]
Generated description
오산대역은 경기도 오산시에 위치한 수도권 전철 1호선의 역으로, 오산대학과 인근 지역을 연결하는 주요 교통 거점이다.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 오산대역 Target entity description: 오산대역은 경기도 오산시에 위치한 수도권 전철 1호선의 역으로, 오산대학과 인근 지역을 연결하는 주요 교통 거점이다.
-
A.
Gwanak Station
Gwanak Station is a railway station in South Korea that serves the city of Anyang and connects it to the broader Seoul metropolitan rail network.
-
B.
Yeongdeungpo Station
Yeongdeungpo Station is a major railway and subway interchange in Seoul, South Korea, serving as an important transportation and commercial hub for the Yeongdeungpo area.
-
C.
Hongik University Station
Hongik University Station is a major subway station in Seoul’s Mapo District, serving the popular Hongdae area known for its universities, nightlife, and arts scene.
-
D.
Suwon Station
Suwon Station is a major railway and subway hub in Suwon, South Korea, serving as a key transit, commercial, and regional transportation center.
-
E.
Seoul National University Station
Seoul National University Station is a major Seoul Metropolitan Subway stop serving the area near Seoul National University in southern Seoul.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b588b88190a88e91d521acbdfe |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed3363f688190a5c728846bea743a |
completed | May 9, 2026, 6:24 a.m. |
| NEDg | Description generation | batch_69fed76d6a888190b44efa490df4b6d0 |
completed | May 9, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feda443c64819087cb16ce742e7cc5 |
completed | May 9, 2026, 6:55 a.m. |
Created at: April 10, 2026, 3:10 a.m.