Triple
T4839106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangnam District |
E108134
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 강남구 |
E108134
|
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: 강남구 | Statement: [Gangnam District, nativeName, 강남구]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 강남구 Context triple: [Gangnam District, nativeName, 강남구]
-
A.
금정구
금정구는 부산광역시 북동부에 위치한 행정구로, 금정산과 범어사 등 자연·문화 유산이 풍부한 주거·교육 중심 지역이다.
-
B.
Gangnam District
chosen
Gangnam District is a wealthy, high-end commercial and residential area in Seoul, South Korea, known for its skyscrapers, luxury shopping, and vibrant nightlife.
-
C.
Seocho District
Seocho District is a major affluent ward in southern Seoul, South Korea, known for its legal institutions, upscale residential areas, and proximity to the Gangnam business district.
-
D.
Seodaemun-gu
Seodaemun-gu is a central district in Seoul, South Korea, known for its major universities, historical sites, and vibrant urban neighborhoods.
-
E.
Yeongdeungpo District
Yeongdeungpo District is a major administrative and commercial area in southwestern Seoul, South Korea, known for its government institutions, business centers, and dense urban development.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ce4a5108190aede620d5dde1f81 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67d449188190a2f02fa30aee4891 |
completed | March 21, 2026, 9:41 a.m. |
Created at: March 20, 2026, 1:25 p.m.