Triple
T2287949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eumseong County |
E51436
|
entity |
| Predicate | hasAdministrativeDivision |
P747
|
FINISHED |
| Object |
Soi-myeon
Soi-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, South Korea.
|
E316896
|
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: Soi-myeon | Statement: [Eumseong County, hasAdministrativeDivision, Soi-myeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soi-myeon Context triple: [Eumseong County, hasAdministrativeDivision, Soi-myeon]
-
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.
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.
-
C.
Joseongeul
Joseongeul is the native Korean alphabetic writing system, more commonly known today as Hangul.
-
D.
Seo-dong
Seo-dong is a neighborhood within Busan’s Geumjeong District in South Korea, known primarily as a residential area with local commerce and community facilities.
-
E.
Maengdong-myeon
Maengdong-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, 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: Soi-myeon Triple: [Eumseong County, hasAdministrativeDivision, Soi-myeon]
Generated description
Soi-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Soi-myeon Target entity description: Soi-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, South Korea.
-
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.
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.
-
C.
Joseongeul
Joseongeul is the native Korean alphabetic writing system, more commonly known today as Hangul.
-
D.
Seo-dong
Seo-dong is a neighborhood within Busan’s Geumjeong District in South Korea, known primarily as a residential area with local commerce and community facilities.
-
E.
Maengdong-myeon
Maengdong-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc2497ce881909b05eb9cec67d9e7 |
completed | March 7, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b108bbc090819092b76eb134aad909 |
completed | March 11, 2026, 6:16 a.m. |
| NEDg | Description generation | batch_69b10b6cead481908ad8ff7e65caebcf |
completed | March 11, 2026, 6:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b10f1ed9e88190ae4b06611d0c772c |
completed | March 11, 2026, 6:43 a.m. |
Created at: March 4, 2026, 7:48 p.m.