Triple
T14762567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seodaemun-gu |
E346906
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 서대문구 |
E346906
|
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: 서대문구 | Statement: [Seodaemun-gu, nativeName, 서대문구]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 서대문구 Context triple: [Seodaemun-gu, nativeName, 서대문구]
-
A.
Dongdaemun-gu
Dongdaemun-gu is a central district in Seoul, South Korea, known for its major commercial areas, historic sites, and the iconic Dongdaemun Design Plaza.
-
B.
Seodaemun-gu
chosen
Seodaemun-gu is a central district in Seoul, South Korea, known for its major universities, historical sites, and vibrant urban neighborhoods.
-
C.
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.
-
D.
금정구
금정구는 부산광역시 북동부에 위치한 행정구로, 금정산과 범어사 등 자연·문화 유산이 풍부한 주거·교육 중심 지역이다.
-
E.
중구
중구는 대한민국 대구광역시의 중심 상업·행정 지역으로, 번화한 도심과 역사·문화 시설이 밀집한 구이다.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f3a1608190b1b17624003a0c7f |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf24c0081909221cb7d761e882f |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:30 a.m.