Triple
T10567313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pusanjin-gu |
E249383
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Jeonpo-dong |
E257406
|
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: Jeonpo-dong | Statement: [Pusanjin-gu, hasSubdivision, Jeonpo-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeonpo-dong Context triple: [Pusanjin-gu, hasSubdivision, Jeonpo-dong]
-
A.
Jeonpo-dong
chosen
Jeonpo-dong is a neighborhood in Busan, South Korea, known for its trendy cafes, boutiques, and vibrant urban culture.
-
B.
Jangjeon-dong
Jangjeon-dong is a neighborhood in Busan, South Korea, known as an administrative and residential center within Geumjeong District.
-
C.
Beomjeon-dong
Beomjeon-dong is a neighborhood (dong) located within Busanjin District in Busan, South Korea.
-
D.
Yongho-dong
Yongho-dong is a neighborhood in Busan, South Korea, known as a coastal residential area within the city's southern region.
-
E.
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.
- 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_69e2d65fc0948190af4356fc9f5004bb |
completed | April 18, 2026, 12:54 a.m. |
Created at: April 6, 2026, 12:36 p.m.