Triple
T7292397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganghwa County |
E164428
|
entity |
| Predicate | hasAdministrativeCenter |
P1474
|
FINISHED |
| Object |
Ganghwa-eup
Ganghwa-eup is the main town and urban hub of Ganghwa County in Incheon, South Korea, serving as its political and economic center.
|
E691919
|
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: Ganghwa-eup | Statement: [Ganghwa County, hasAdministrativeCenter, Ganghwa-eup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ganghwa-eup Context triple: [Ganghwa County, hasAdministrativeCenter, Ganghwa-eup]
-
A.
Yeonsu-gu
Yeonsu-gu is an administrative district of Incheon, South Korea, known for its coastal location, modern residential areas, and proximity to the Songdo International Business District.
-
B.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
C.
Gyeyang-gu
Gyeyang-gu is an administrative district of Incheon, South Korea, known for its mix of residential areas, historical sites, and access to natural attractions like Gyeyang Mountain.
-
D.
Sasang-gu
Sasang-gu is an administrative district in Busan, South Korea, known for its transportation hubs, industrial areas, and mixed residential-commercial neighborhoods.
-
E.
Dong-gu
Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
- 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: Ganghwa-eup Triple: [Ganghwa County, hasAdministrativeCenter, Ganghwa-eup]
Generated description
Ganghwa-eup is the main town and urban hub of Ganghwa County in Incheon, South Korea, serving as its political and economic center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ganghwa-eup Target entity description: Ganghwa-eup is the main town and urban hub of Ganghwa County in Incheon, South Korea, serving as its political and economic center.
-
A.
Yeonsu-gu
Yeonsu-gu is an administrative district of Incheon, South Korea, known for its coastal location, modern residential areas, and proximity to the Songdo International Business District.
-
B.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
C.
Gyeyang-gu
Gyeyang-gu is an administrative district of Incheon, South Korea, known for its mix of residential areas, historical sites, and access to natural attractions like Gyeyang Mountain.
-
D.
Sasang-gu
Sasang-gu is an administrative district in Busan, South Korea, known for its transportation hubs, industrial areas, and mixed residential-commercial neighborhoods.
-
E.
Dong-gu
Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb6fc5788190b1b339d051f93c22 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9c89d62c08190b575d7e1058afbeb |
completed | March 30, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69c9c9347bf08190a0b7db37ad510785 |
completed | March 30, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c9c98bbab88190801098d78e68de54 |
completed | March 30, 2026, 12:53 a.m. |
Created at: March 27, 2026, 3 p.m.