Triple

T1586640
Position Surface form Disambiguated ID Type / Status
Subject Busanjin District E34080 entity
Predicate contains P35 FINISHED
Object Seomyeon
Seomyeon is a major commercial and entertainment hub in central Busan, South Korea, known for its dense concentration of shops, restaurants, bars, and nightlife.
 E252412 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: Seomyeon | Statement: [Busanjin District, contains, Seomyeon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Seomyeon
Context triple: [Busanjin District, contains, Seomyeon]
  • A. Yeouido-dong
    Yeouido-dong is a major financial and business district in Seoul, South Korea, known for its skyscrapers, corporate headquarters, and role as a political and economic hub.
  • B. Suyeong-dong
    Suyeong-dong is a neighborhood in Busan, South Korea, known as part of the urban area within Suyeong District.
  • C. Jung-gu
    Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
  • D. Jung-gu
    Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
  • E. Hwamyeong-dong
    Hwamyeong-dong is a neighborhood in Busan, South Korea, known as a residential and commercial area within the city's urban landscape.
  • 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: Seomyeon
Triple: [Busanjin District, contains, Seomyeon]
Generated description
Seomyeon is a major commercial and entertainment hub in central Busan, South Korea, known for its dense concentration of shops, restaurants, bars, and nightlife.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Seomyeon
Target entity description: Seomyeon is a major commercial and entertainment hub in central Busan, South Korea, known for its dense concentration of shops, restaurants, bars, and nightlife.
  • A. Yeouido-dong
    Yeouido-dong is a major financial and business district in Seoul, South Korea, known for its skyscrapers, corporate headquarters, and role as a political and economic hub.
  • B. Suyeong-dong
    Suyeong-dong is a neighborhood in Busan, South Korea, known as part of the urban area within Suyeong District.
  • C. Jung-gu
    Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
  • D. Jung-gu
    Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
  • E. Hwamyeong-dong
    Hwamyeong-dong is a neighborhood in Busan, South Korea, known as a residential and commercial area within the city's urban landscape.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908f3b5f48190bd5eff3ce81c5ffb completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7ed1080081909a931e4d045edd83 completed March 9, 2026, 8:03 a.m.
NEDg Description generation batch_69ae7faa64e48190b82e48165a931598 completed March 9, 2026, 8:07 a.m.
NED2 Entity disambiguation (via description) batch_69ae801a87a88190ae461ca164b358a4 completed March 9, 2026, 8:08 a.m.
Created at: March 4, 2026, 7:27 p.m.