Triple
T20258030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Chungcheong Province |
E498754
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Boryeong
Boryeong is a coastal city in South Korea best known for its annual mud festival held on the beaches of Daecheon.
|
E1420843
|
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: Boryeong | Statement: [South Chungcheong Province, hasMajorCity, Boryeong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boryeong Context triple: [South Chungcheong Province, hasMajorCity, Boryeong]
-
A.
Mokneung
Mokneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
-
B.
Jeongeup
Jeongeup is a city in South Korea known for its location in North Jeolla Province and its cultural and historical heritage.
-
C.
Seongsan-eup
Seongsan-eup is a coastal town on South Korea’s Jeju Island known for its scenic landscapes and proximity to the volcanic tuff cone Seongsan Ilchulbong, a UNESCO World Heritage site.
-
D.
Yeoju
Yeoju is a city in South Korea known for its rich historical heritage, including royal tombs and ceramics, and its scenic riverside landscapes.
-
E.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
- 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: Boryeong Triple: [South Chungcheong Province, hasMajorCity, Boryeong]
Generated description
Boryeong is a coastal city in South Korea best known for its annual mud festival held on the beaches of Daecheon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Boryeong Target entity description: Boryeong is a coastal city in South Korea best known for its annual mud festival held on the beaches of Daecheon.
-
A.
Mokneung
Mokneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
-
B.
Jeongeup
Jeongeup is a city in South Korea known for its location in North Jeolla Province and its cultural and historical heritage.
-
C.
Seongsan-eup
Seongsan-eup is a coastal town on South Korea’s Jeju Island known for its scenic landscapes and proximity to the volcanic tuff cone Seongsan Ilchulbong, a UNESCO World Heritage site.
-
D.
Yeoju
Yeoju is a city in South Korea known for its rich historical heritage, including royal tombs and ceramics, and its scenic riverside landscapes.
-
E.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674c7296c819092860942de8f28d5 |
completed | April 20, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08552c65488190922fc54374072e69 |
completed | May 16, 2026, 11:29 a.m. |
| NEDg | Description generation | batch_6a0855d7d87481908ff14d53a2ac94f7 |
completed | May 16, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0856da3e748190866c328a6c61b3d8 |
completed | May 16, 2026, 11:36 a.m. |
Created at: April 11, 2026, 11:41 p.m.