Triple
T10567317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pusanjin-gu |
E249383
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Busanjin-dong |
E255726
|
NE FINISHED |
How this triple was built (2 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: Busanjin-dong | Statement: [Pusanjin-gu, hasSubdivision, Busanjin-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Busanjin-dong Context triple: [Pusanjin-gu, hasSubdivision, Busanjin-dong]
-
A.
Bupyeong-dong
Bupyeong-dong is a central neighborhood and administrative hub within Bupyeong District in Incheon, South Korea.
-
B.
Bangbae-dong
Bangbae-dong is a residential and commercial neighborhood in southern Seoul, South Korea, known for its convenient urban amenities and location within the affluent Seocho area.
-
C.
Bujeon-dong
chosen
Bujeon-dong is a neighborhood in Busan, South Korea, known as a busy commercial and transportation hub with markets, shops, and access to major train and subway lines.
-
D.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
E.
Osan-dong
Osan-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea, functioning as a local administrative and residential area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ef5848190b76d671ea2d26314 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c7b89a808190af9b2d4f37ad9012 |
completed | April 18, 2026, 6:04 p.m. |
Created at: April 6, 2026, 12:36 p.m.