Triple
T7131353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jung District, Busan |
E166194
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object |
Jung-gu
Jung-gu is a central district of Busan, South Korea, known for its historic markets, port-side location, and dense urban commercial areas.
|
E691077
|
NE FINISHED |
How this triple was built (4 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: Jung-gu | Statement: [Jung District, Busan, officialName, Jung-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jung-gu Context triple: [Jung District, Busan, officialName, Jung-gu]
-
A.
Jung-gu
Jung-gu is a central urban district of Daegu, South Korea, known for its dense commercial areas, historic sites, and administrative importance.
-
B.
Jung-gu
Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
-
C.
Jung-gu
Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
-
D.
Jung-gu
Jung-gu is a central urban district name used in several major South Korean cities, typically encompassing key commercial, administrative, and cultural areas.
-
E.
Chongno-gu
Chongno-gu is a central district in Seoul, South Korea, known as the historic and cultural heart of the city, home to major palaces, government institutions, and traditional markets.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jung-gu Triple: [Jung District, Busan, officialName, Jung-gu]
Generated description
Jung-gu is a central district of Busan, South Korea, known for its historic markets, port-side location, and dense urban commercial areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jung-gu Target entity description: Jung-gu is a central district of Busan, South Korea, known for its historic markets, port-side location, and dense urban commercial areas.
-
A.
Jung-gu
Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
-
B.
Jung-gu
Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
-
C.
Jung-gu
Jung-gu is a central urban district of Daegu, South Korea, known for its dense commercial areas, historic sites, and administrative importance.
-
D.
Jung-gu
Jung-gu is a central urban district name used in several major South Korean cities, typically encompassing key commercial, administrative, and cultural areas.
-
E.
Chongno-gu
Chongno-gu is a central district in Seoul, South Korea, known as the historic and cultural heart of the city, home to major palaces, government institutions, and traditional markets.
- F. None of above. chosen
Provenance (5 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66f15b88190bc1fb0f0a8af16a6 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9660842888190a9d37a5fd1830ccd |
completed | March 29, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_69c966ceec808190ac66e8c2d6e876b5 |
completed | March 29, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c96800354c8190a71c5a3802de5373 |
completed | March 29, 2026, 5:57 p.m. |
Created at: March 27, 2026, 2:44 p.m.