Triple
T6570306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeonsu District |
E155416
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Songdo-dong
Songdo-dong is a modern waterfront neighborhood in Incheon, South Korea, best known for hosting the high-tech, master-planned Songdo International Business District.
|
E637403
|
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: Songdo-dong | Statement: [Yeonsu District, hasNeighborhood, Songdo-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Songdo-dong Context triple: [Yeonsu District, hasNeighborhood, Songdo-dong]
-
A.
Gocheon-dong
Gocheon-dong is a neighborhood (dong) that forms part of the city of Osan in Gyeonggi Province, South Korea.
-
B.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
C.
Nonhyeon-dong
Nonhyeon-dong is a neighborhood in Seoul, South Korea, known for its mix of residential areas, commercial streets, and proximity to major business and shopping districts.
-
D.
Suyeong-dong
Suyeong-dong is a neighborhood in Busan, South Korea, known as part of the urban area within Suyeong District.
-
E.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, 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: Songdo-dong Triple: [Yeonsu District, hasNeighborhood, Songdo-dong]
Generated description
Songdo-dong is a modern waterfront neighborhood in Incheon, South Korea, best known for hosting the high-tech, master-planned Songdo International Business District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Songdo-dong Target entity description: Songdo-dong is a modern waterfront neighborhood in Incheon, South Korea, best known for hosting the high-tech, master-planned Songdo International Business District.
-
A.
Gocheon-dong
Gocheon-dong is a neighborhood (dong) that forms part of the city of Osan in Gyeonggi Province, South Korea.
-
B.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
C.
Nonhyeon-dong
Nonhyeon-dong is a neighborhood in Seoul, South Korea, known for its mix of residential areas, commercial streets, and proximity to major business and shopping districts.
-
D.
Suyeong-dong
Suyeong-dong is a neighborhood in Busan, South Korea, known as part of the urban area within Suyeong District.
-
E.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, 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_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_69c77518ecf08190825f64b47d575fba |
completed | March 28, 2026, 6:28 a.m. |
| NEDg | Description generation | batch_69c77725eeb881909433ec7318c0dcca |
completed | March 28, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c77768aa6c81909b6cf5c62780bb8d |
completed | March 28, 2026, 6:38 a.m. |
Created at: March 27, 2026, 1:53 p.m.