Triple
T1557749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suyeong District |
E33247
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object |
Suyŏng-gu
Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
|
E238309
|
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: Suyŏng-gu | Statement: [Suyeong District, romanization, Suyŏng-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suyŏng-gu Context triple: [Suyeong District, romanization, Suyŏng-gu]
-
A.
Seo-gu
Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
-
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.
Ami-dong
Ami-dong is a neighborhood in Busan, South Korea, known in part for hosting a campus of Pusan National University.
-
D.
Yeonsu District
Yeonsu District is a coastal administrative district in Incheon, South Korea, known for its modern residential areas, educational institutions, and proximity to the Songdo International Business District.
-
E.
Daedeok-gu
Daedeok-gu is a district in the city of Daejeon, South Korea, known for encompassing parts of the country’s major research and science complex.
- 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: Suyŏng-gu Triple: [Suyeong District, romanization, Suyŏng-gu]
Generated description
Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suyŏng-gu Target entity description: Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
-
A.
Seo-gu
Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
-
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.
Ami-dong
Ami-dong is a neighborhood in Busan, South Korea, known in part for hosting a campus of Pusan National University.
-
D.
Yeonsu District
Yeonsu District is a coastal administrative district in Incheon, South Korea, known for its modern residential areas, educational institutions, and proximity to the Songdo International Business District.
-
E.
Daedeok-gu
Daedeok-gu is a district in the city of Daejeon, South Korea, known for encompassing parts of the country’s major research and science complex.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9088355048190adad5ea2bb558d13 |
completed | March 5, 2026, 4:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58ac128881909a2e75524682c1c9 |
completed | March 9, 2026, 5:20 a.m. |
| NEDg | Description generation | batch_69ae5944543081909622e93012a31766 |
completed | March 9, 2026, 5:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae59d0fb688190858c764517aea035 |
completed | March 9, 2026, 5:25 a.m. |
Created at: March 4, 2026, 7:27 p.m.