Triple
T4130940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Chaek |
E85039
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
김책
김책은 일제강점기와 한국전쟁 시기에 활동한 북한의 혁명가이자 군사 지휘관으로, 북한 초기 정권 수립에 기여한 인물이다.
|
E414736
|
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: 김책 | Statement: [Kim Chaek, nativeName, 김책]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 김책 Context triple: [Kim Chaek, nativeName, 김책]
-
A.
Bucheon
Bucheon is a major satellite city of Seoul in South Korea, known for its dense urban environment and cultural attractions such as the Bucheon International Fantastic Film Festival.
-
B.
Gapcheon
Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
-
C.
Anseong
Anseong is a city in Gyeonggi Province, South Korea, known for its traditional culture, agricultural heritage, and annual Baudeogi Festival.
-
D.
Dangjin
Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
-
E.
Hwaseong
Hwaseong is a city in Gyeonggi Province, South Korea, known for its rapid industrial growth and proximity to major urban centers like Suwon and Seoul.
- 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: 김책 Triple: [Kim Chaek, nativeName, 김책]
Generated description
김책은 일제강점기와 한국전쟁 시기에 활동한 북한의 혁명가이자 군사 지휘관으로, 북한 초기 정권 수립에 기여한 인물이다.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 김책 Target entity description: 김책은 일제강점기와 한국전쟁 시기에 활동한 북한의 혁명가이자 군사 지휘관으로, 북한 초기 정권 수립에 기여한 인물이다.
-
A.
Bucheon
Bucheon is a major satellite city of Seoul in South Korea, known for its dense urban environment and cultural attractions such as the Bucheon International Fantastic Film Festival.
-
B.
Gapcheon
Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
-
C.
Anseong
Anseong is a city in Gyeonggi Province, South Korea, known for its traditional culture, agricultural heritage, and annual Baudeogi Festival.
-
D.
Dangjin
Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
-
E.
Hwaseong
Hwaseong is a city in Gyeonggi Province, South Korea, known for its rapid industrial growth and proximity to major urban centers like Suwon and Seoul.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af021f6a508190b8ac1e0d8b859f74 |
completed | March 9, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576c26d4c81909b8be74855cbd03f |
completed | March 14, 2026, 2:54 p.m. |
| NEDg | Description generation | batch_69b577c2b784819096d8218dd1c1478d |
completed | March 14, 2026, 2:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5782cc448819080e306952da24ac0 |
completed | March 14, 2026, 3:01 p.m. |
Created at: March 9, 2026, 3:42 p.m.