Triple

T1655516
Position Surface form Disambiguated ID Type / Status
Subject Geumjeong District E35789 entity
Predicate contains P35 FINISHED
Object Nopo-dong
Nopo-dong is a neighborhood in Busan, South Korea, known as a major transportation hub and gateway to the city.
E187743 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: Nopo-dong | Statement: [Geumjeong District, contains, Nopo-dong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nopo-dong
Context triple: [Geumjeong District, contains, Nopo-dong]
  • A. Mangyongdae
    Mangyongdae is a historic district in Pyongyang, North Korea, known as the birthplace and commemorative site of the country's founding leader, Kim Il Sung.
  • B. Ami-dong
    Ami-dong is a neighborhood in Busan, South Korea, known in part for hosting a campus of Pusan National University.
  • C. Neryungri
    Neryungri is a major coal-mining and industrial city in southeastern Siberia, Russia, known as one of the key urban centers of the Sakha Republic (Yakutia).
  • D. Gamjeon-dong
    Gamjeon-dong is a neighborhood in the Sasang District of Busan, South Korea, known as a residential and commercial area within the city.
  • E. Gwaebeop-dong
    Gwaebeop-dong is a neighborhood in Busan, South Korea, known as an administrative subdivision of the city's Sasang District.
  • 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: Nopo-dong
Triple: [Geumjeong District, contains, Nopo-dong]
Generated description
Nopo-dong is a neighborhood in Busan, South Korea, known as a major transportation hub and gateway to the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nopo-dong
Target entity description: Nopo-dong is a neighborhood in Busan, South Korea, known as a major transportation hub and gateway to the city.
  • A. Mangyongdae
    Mangyongdae is a historic district in Pyongyang, North Korea, known as the birthplace and commemorative site of the country's founding leader, Kim Il Sung.
  • B. Ami-dong
    Ami-dong is a neighborhood in Busan, South Korea, known in part for hosting a campus of Pusan National University.
  • C. Neryungri
    Neryungri is a major coal-mining and industrial city in southeastern Siberia, Russia, known as one of the key urban centers of the Sakha Republic (Yakutia).
  • D. Gamjeon-dong
    Gamjeon-dong is a neighborhood in the Sasang District of Busan, South Korea, known as a residential and commercial area within the city.
  • E. Gwaebeop-dong
    Gwaebeop-dong is a neighborhood in Busan, South Korea, known as an administrative subdivision of the city's Sasang District.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb4535180819088e3bdaa591dcdbd completed March 7, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6821d18c8190b411bb031c142580 completed March 8, 2026, 12:14 p.m.
NEDg Description generation batch_69ad68a9769081908a0748b8d02b8379 completed March 8, 2026, 12:16 p.m.
NED2 Entity disambiguation (via description) batch_69ad692d61288190ad0c0265f49643ac completed March 8, 2026, 12:18 p.m.
Created at: March 4, 2026, 7:29 p.m.