Triple

T14814320
Position Surface form Disambiguated ID Type / Status
Subject Seongbuk District E348269 entity
Predicate contains P35 FINISHED
Object Donam-dong
Donam-dong is a neighborhood in northern Seoul, South Korea, known as a residential and commercial area within the city's Seongbuk District.
E1176108 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: Donam-dong | Statement: [Seongbuk District, contains, Donam-dong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donam-dong
Context triple: [Seongbuk District, contains, Donam-dong]
  • A. Jangnim-dong
    Jangnim-dong is a neighborhood in Busan, South Korea, known as a residential and industrial area within the city's southern coastal region.
  • B. Sogyeok-dong
    Sogyeok-dong is a neighborhood in central Seoul, South Korea, known for its traditional Korean houses (hanok), art galleries, and proximity to historic palaces.
  • C. Sasang-dong
    Sasang-dong is a neighborhood in Busan, South Korea, known as an urban residential and commercial area within the city's Sasang District.
  • D. Beomil-dong
    Beomil-dong is a neighborhood in Dong-gu, Busan, South Korea, known as a residential and commercial area within the city.
  • E. Millak-dong
    Millak-dong is a coastal neighborhood in Busan, South Korea, known for its proximity to Gwangalli Beach and vibrant urban atmosphere.
  • 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: Donam-dong
Triple: [Seongbuk District, contains, Donam-dong]
Generated description
Donam-dong is a neighborhood in northern Seoul, South Korea, known as a residential and commercial area within the city's Seongbuk District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Donam-dong
Target entity description: Donam-dong is a neighborhood in northern Seoul, South Korea, known as a residential and commercial area within the city's Seongbuk District.
  • A. Jangnim-dong
    Jangnim-dong is a neighborhood in Busan, South Korea, known as a residential and industrial area within the city's southern coastal region.
  • B. Sogyeok-dong
    Sogyeok-dong is a neighborhood in central Seoul, South Korea, known for its traditional Korean houses (hanok), art galleries, and proximity to historic palaces.
  • C. Sasang-dong
    Sasang-dong is a neighborhood in Busan, South Korea, known as an urban residential and commercial area within the city's Sasang District.
  • D. Beomil-dong
    Beomil-dong is a neighborhood in Dong-gu, Busan, South Korea, known as a residential and commercial area within the city.
  • E. Millak-dong
    Millak-dong is a coastal neighborhood in Busan, South Korea, known for its proximity to Gwangalli Beach and vibrant urban atmosphere.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe0e89c81908c0e1fe2bc3ebcfc completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff908410548190ada5d4f71d52919b completed May 9, 2026, 7:52 p.m.
NEDg Description generation batch_69ff9118272c8190a7b33fb312f37d39 completed May 9, 2026, 7:55 p.m.
NED2 Entity disambiguation (via description) batch_69ff9176f8208190ad88791592b35b72 completed May 9, 2026, 7:56 p.m.
Created at: April 10, 2026, 1:48 a.m.