Triple
T7261137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bupyeong District |
E159653
|
entity |
| Predicate | hasRomanizedName |
P2508
|
FINISHED |
| Object | Bupyeong-gu |
E159653
|
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: Bupyeong-gu | Statement: [Bupyeong District, hasRomanizedName, Bupyeong-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bupyeong-gu Context triple: [Bupyeong District, hasRomanizedName, Bupyeong-gu]
-
A.
Yeonsu-gu
Yeonsu-gu is an administrative district of Incheon, South Korea, known for its coastal location, modern residential areas, and proximity to the Songdo International Business District.
-
B.
Bupyeong District
chosen
Bupyeong District is a populous urban district of Incheon, South Korea, known as a major residential, commercial, and transportation hub in the metropolitan area.
-
C.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
D.
Eunpyeong-gu
Eunpyeong-gu is a district in northwestern Seoul, South Korea, known for its mix of urban residential areas and access to nearby mountains and temples.
-
E.
Pusanjin-gu
Pusanjin-gu is a central urban district of Busan, South Korea, known for its major commercial areas, transportation hubs, and dense residential neighborhoods.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac79fd081909274aa10ffb192aa |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9abd319048190a24be5112c810489 |
completed | March 29, 2026, 10:46 p.m. |
Created at: March 27, 2026, 2:57 p.m.