Triple

T17242562
Position Surface form Disambiguated ID Type / Status
Subject Kim Chaek City E418537 entity
Predicate formerName P65 FINISHED
Object Sŏngjin
Sŏngjin is the former name of Kim Chaek City, an industrial port city on North Korea’s east coast.
 E1258545 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: Sŏngjin | Statement: [Kim Chaek City, formerName, Sŏngjin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sŏngjin
Context triple: [Kim Chaek City, formerName, Sŏngjin]
  • A. Phyongwon
    Phyongwon is a city in North Korea known as an administrative and agricultural center within North Pyongan Province.
  • B. Nakchhong
    Nakchhong is a traditional ritual specialist and religious officiant within the Kirat Mundhum indigenous belief system.
  • C. Kyongsong
    Kyongsong is a coastal town and county-level city in northeastern North Korea known for its hot springs and location along the Sea of Japan (East Sea).
  • 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. Sokcho
    Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
  • 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: Sŏngjin
Triple: [Kim Chaek City, formerName, Sŏngjin]
Generated description
Sŏngjin is the former name of Kim Chaek City, an industrial port city on North Korea’s east coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sŏngjin
Target entity description: Sŏngjin is the former name of Kim Chaek City, an industrial port city on North Korea’s east coast.
  • A. Phyongwon
    Phyongwon is a city in North Korea known as an administrative and agricultural center within North Pyongan Province.
  • B. Nakchhong
    Nakchhong is a traditional ritual specialist and religious officiant within the Kirat Mundhum indigenous belief system.
  • C. Kyongsong
    Kyongsong is a coastal town and county-level city in northeastern North Korea known for its hot springs and location along the Sea of Japan (East Sea).
  • 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. Sokcho
    Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e21003c81908c884a3c8712676a completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170f388608190b709b1c228a7ba29 completed May 11, 2026, 6:02 a.m.
NEDg Description generation batch_6a01718311a48190890c770f571852c8 completed May 11, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a01721f5b9081909a8bc817ba0a5986 completed May 11, 2026, 6:07 a.m.
Created at: April 10, 2026, 5:39 a.m.