Triple

T17091531
Position Surface form Disambiguated ID Type / Status
Subject North Hamgyong Province E414737 entity
Predicate hasMajorCity P316 FINISHED
Object Musan
Musan is a mining town in northeastern North Korea known for its large iron ore deposits and proximity to the Chinese border.
 E1253146 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: Musan | Statement: [North Hamgyong Province, hasMajorCity, Musan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Musan
Context triple: [North Hamgyong Province, hasMajorCity, Musan]
  • A. Gwangalli
    Gwangalli is a coastal neighborhood in Busan, South Korea, best known for its sandy beach, vibrant nightlife, and scenic views of the nearby Gwangan Bridge.
  • B. Odaesan
    Odaesan is a prominent mountain in South Korea known for its scenic national park, rich biodiversity, and important Buddhist temples such as Woljeongsa.
  • C. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • D. Sungsang
    Sungsang is a coastal village in South Sumatra, Indonesia, known as a fishing and port settlement near the mouth of the Musi River.
  • E. Haeju
    Haeju is a coastal city in southwestern North Korea, historically significant as a regional center and port on the Yellow Sea.
  • 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: Musan
Triple: [North Hamgyong Province, hasMajorCity, Musan]
Generated description
Musan is a mining town in northeastern North Korea known for its large iron ore deposits and proximity to the Chinese border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Musan
Target entity description: Musan is a mining town in northeastern North Korea known for its large iron ore deposits and proximity to the Chinese border.
  • A. Gwangalli
    Gwangalli is a coastal neighborhood in Busan, South Korea, best known for its sandy beach, vibrant nightlife, and scenic views of the nearby Gwangan Bridge.
  • B. Odaesan
    Odaesan is a prominent mountain in South Korea known for its scenic national park, rich biodiversity, and important Buddhist temples such as Woljeongsa.
  • C. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • D. Sungsang
    Sungsang is a coastal village in South Sumatra, Indonesia, known as a fishing and port settlement near the mouth of the Musi River.
  • E. Haeju
    Haeju is a coastal city in southwestern North Korea, historically significant as a regional center and port on the Yellow Sea.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbfa09b08190be4303dd0d174feb completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0141422d6c819086dc98988c0851d9 completed May 11, 2026, 2:38 a.m.
NEDg Description generation batch_6a01437dd094819093603356fa2c2582 completed May 11, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_6a014416c6a08190aeca937990d2b5a2 completed May 11, 2026, 2:51 a.m.
Created at: April 10, 2026, 5:35 a.m.