Triple

T17017894
Position Surface form Disambiguated ID Type / Status
Subject Seoul Metropolitan Government E412868 entity
Predicate hasSubdivision P747 FINISHED
Object Jung-gu
Jung-gu is a central district of Seoul, South Korea, known as a major hub for business, shopping, and historic sites.
 E1274224 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: Jung-gu | Statement: [Seoul Metropolitan Government, hasSubdivision, Jung-gu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jung-gu
Context triple: [Seoul Metropolitan Government, hasSubdivision, Jung-gu]
  • A. 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.
  • B. Jung-gu
    Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
  • C. Jung-gu
    Jung-gu is a central urban district of Daegu, South Korea, known for its dense commercial areas, historic sites, and administrative importance.
  • D. Jung-gu
    Jung-gu is a central district of Busan, South Korea, known for its historic markets, port-side location, and dense urban commercial areas.
  • E. Jung-gu
    Jung-gu is a central urban district name used in several major South Korean cities, typically encompassing key commercial, administrative, and cultural areas.
  • 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: Jung-gu
Triple: [Seoul Metropolitan Government, hasSubdivision, Jung-gu]
Generated description
Jung-gu is a central district of Seoul, South Korea, known as a major hub for business, shopping, and historic sites.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jung-gu
Target entity description: Jung-gu is a central district of Seoul, South Korea, known as a major hub for business, shopping, and historic sites.
  • A. 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.
  • B. Jung-gu
    Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
  • C. Jung-gu
    Jung-gu is a central urban district of Daegu, South Korea, known for its dense commercial areas, historic sites, and administrative importance.
  • D. Jung-gu
    Jung-gu is a central urban district name used in several major South Korean cities, typically encompassing key commercial, administrative, and cultural areas.
  • E. Jung-gu
    Jung-gu is a central district of Busan, South Korea, known for its historic markets, port-side location, and dense urban commercial areas.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d480a58c8190a3912d26debb4311 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01c927c7c4819091046c686600db9f completed May 11, 2026, 12:18 p.m.
NEDg Description generation batch_6a01cd5d88948190b347948b1f0584c0 completed May 11, 2026, 12:36 p.m.
NED2 Entity disambiguation (via description) batch_6a01cdca32e08190aeae5315494f9ab3 completed May 11, 2026, 12:38 p.m.
Created at: April 10, 2026, 5:33 a.m.