Triple
T14665944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinchon-dong |
E344372
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object |
Nogosan-dong
Nogosan-dong is a neighborhood in Seoul, South Korea, known for its proximity to the bustling Sinchon area and its mix of residential streets and urban amenities.
|
E1126435
|
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: Nogosan-dong | Statement: [Sinchon-dong, adjacentTo, Nogosan-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nogosan-dong Context triple: [Sinchon-dong, adjacentTo, Nogosan-dong]
-
A.
Yongho-dong
Yongho-dong is a neighborhood in Busan, South Korea, known as a coastal residential area within the city's southern region.
-
B.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
C.
Bupyeong-dong
Bupyeong-dong is a neighborhood in Busan, South Korea, known for its traditional markets, narrow alleyways, and vibrant local commerce.
-
D.
Bupyeong-dong
Bupyeong-dong is a central neighborhood and administrative hub within Bupyeong District in Incheon, South Korea.
-
E.
Okryeon-dong
Okryeon-dong is a neighborhood located within Yeonsu District in Incheon, South Korea.
- 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: Nogosan-dong Triple: [Sinchon-dong, adjacentTo, Nogosan-dong]
Generated description
Nogosan-dong is a neighborhood in Seoul, South Korea, known for its proximity to the bustling Sinchon area and its mix of residential streets and urban amenities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nogosan-dong Target entity description: Nogosan-dong is a neighborhood in Seoul, South Korea, known for its proximity to the bustling Sinchon area and its mix of residential streets and urban amenities.
-
A.
Yongho-dong
Yongho-dong is a neighborhood in Busan, South Korea, known as a coastal residential area within the city's southern region.
-
B.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
C.
Bupyeong-dong
Bupyeong-dong is a central neighborhood and administrative hub within Bupyeong District in Incheon, South Korea.
-
D.
Bupyeong-dong
Bupyeong-dong is a neighborhood in Busan, South Korea, known for its traditional markets, narrow alleyways, and vibrant local commerce.
-
E.
Okryeon-dong
Okryeon-dong is a neighborhood located within Yeonsu District in Incheon, South Korea.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54c69f8819080a37161deecfba8 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe729f894881908647da558bef1031 |
completed | May 8, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69fe732a6e148190814cf358bafb76b4 |
completed | May 8, 2026, 11:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe73fe39508190aa9b78617b729b51 |
completed | May 8, 2026, 11:38 p.m. |
Created at: April 10, 2026, 1:27 a.m.