Triple
T7767712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangseo District, Busan |
E178990
|
entity |
| Predicate | administrativeSeat |
P21613
|
FINISHED |
| Object |
Gangdong-dong
Gangdong-dong is a neighborhood in Busan, South Korea, serving as the central administrative hub of the city's Gangseo District.
|
E687249
|
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: Gangdong-dong | Statement: [Gangseo District, Busan, administrativeSeat, Gangdong-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gangdong-dong Context triple: [Gangseo District, Busan, administrativeSeat, Gangdong-dong]
-
A.
Won-dong
Won-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
B.
Sudogwon
Sudogwon is the Seoul Capital Area of South Korea, encompassing Seoul, Incheon, and surrounding Gyeonggi Province as the country’s largest and most populous metropolitan region.
-
C.
Itaewon
Itaewon is a vibrant multicultural district in Seoul known for its international cuisine, nightlife, and diverse expatriate community.
-
D.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
E.
Singil-dong
Singil-dong is a neighborhood (dong) in Seoul, South Korea, located within the city's southwestern Yeongdeungpo District.
- 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: Gangdong-dong Triple: [Gangseo District, Busan, administrativeSeat, Gangdong-dong]
Generated description
Gangdong-dong is a neighborhood in Busan, South Korea, serving as the central administrative hub of the city's Gangseo District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gangdong-dong Target entity description: Gangdong-dong is a neighborhood in Busan, South Korea, serving as the central administrative hub of the city's Gangseo District.
-
A.
Won-dong
Won-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
B.
Sudogwon
Sudogwon is the Seoul Capital Area of South Korea, encompassing Seoul, Incheon, and surrounding Gyeonggi Province as the country’s largest and most populous metropolitan region.
-
C.
Itaewon
Itaewon is a vibrant multicultural district in Seoul known for its international cuisine, nightlife, and diverse expatriate community.
-
D.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
E.
Singil-dong
Singil-dong is a neighborhood (dong) in Seoul, South Korea, located within the city's southwestern Yeongdeungpo District.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c70435b7f88190a5e68e6ae701c58f |
completed | March 27, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7e4976c81909ff34dcdcae96999 |
completed | March 29, 2026, 6:34 a.m. |
| NEDg | Description generation | batch_69c8c8b75b848190a67de2040d563f86 |
completed | March 29, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8c941814081909d299df5cd714c71 |
completed | March 29, 2026, 6:40 a.m. |
Created at: March 27, 2026, 4:11 p.m.