Triple
T5575188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jongno-gu |
E146300
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Sogyeok-dong
Sogyeok-dong is a neighborhood in central Seoul, South Korea, known for its traditional Korean houses (hanok), art galleries, and proximity to historic palaces.
|
E570221
|
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: Sogyeok-dong | Statement: [Jongno-gu, contains, Sogyeok-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sogyeok-dong Context triple: [Jongno-gu, contains, Sogyeok-dong]
-
A.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
B.
Sasang-dong
Sasang-dong is a neighborhood in Busan, South Korea, known as an urban residential and commercial area within the city's Sasang District.
-
C.
Beomjeon-dong
Beomjeon-dong is a neighborhood (dong) located within Busanjin District in Busan, South Korea.
-
D.
Yeoksam-dong
Yeoksam-dong is a major commercial and residential neighborhood in Seoul, South Korea, known for its dense cluster of corporate offices, tech companies, and vibrant urban amenities.
-
E.
Gwangan-dong
Gwangan-dong is a coastal neighborhood in Busan, South Korea, best known for Gwangalli Beach and its views of the illuminated Gwangan Bridge.
- 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: Sogyeok-dong Triple: [Jongno-gu, contains, Sogyeok-dong]
Generated description
Sogyeok-dong is a neighborhood in central Seoul, South Korea, known for its traditional Korean houses (hanok), art galleries, and proximity to historic palaces.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sogyeok-dong Target entity description: Sogyeok-dong is a neighborhood in central Seoul, South Korea, known for its traditional Korean houses (hanok), art galleries, and proximity to historic palaces.
-
A.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
B.
Sasang-dong
Sasang-dong is a neighborhood in Busan, South Korea, known as an urban residential and commercial area within the city's Sasang District.
-
C.
Beomjeon-dong
Beomjeon-dong is a neighborhood (dong) located within Busanjin District in Busan, South Korea.
-
D.
Yeoksam-dong
Yeoksam-dong is a major commercial and residential neighborhood in Seoul, South Korea, known for its dense cluster of corporate offices, tech companies, and vibrant urban amenities.
-
E.
Gwangan-dong
Gwangan-dong is a coastal neighborhood in Busan, South Korea, best known for Gwangalli Beach and its views of the illuminated Gwangan Bridge.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02067e8d8819090a006cb266da5fe |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1351fb4a88190bb12f3a5f8cd92ac |
completed | March 23, 2026, 12:42 p.m. |
| NEDg | Description generation | batch_69c1369fb3648190874e7bbe4a6fd737 |
completed | March 23, 2026, 12:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c136fad48881908b449b8b411c3fc8 |
completed | March 23, 2026, 12:50 p.m. |
Created at: March 22, 2026, 3:37 p.m.