Triple

T2287943
Position Surface form Disambiguated ID Type / Status
Subject Eumseong County E51436 entity
Predicate hasAdministrativeDivision P747 FINISHED
Object Geumwang-eup
Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
E261016 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: Geumwang-eup | Statement: [Eumseong County, hasAdministrativeDivision, Geumwang-eup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geumwang-eup
Context triple: [Eumseong County, hasAdministrativeDivision, Geumwang-eup]
  • A. Eumseong-eup
    Eumseong-eup is the main urban township and administrative center of Eumseong County in North Chungcheong Province, South Korea.
  • B. Gamgok-myeon
    Gamgok-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, South Korea.
  • C. Suyŏng-gu
    Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
  • D. Daedeok-gu
    Daedeok-gu is a district in the city of Daejeon, South Korea, known for encompassing parts of the country’s major research and science complex.
  • E. Seo-gu
    Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
  • 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: Geumwang-eup
Triple: [Eumseong County, hasAdministrativeDivision, Geumwang-eup]
Generated description
Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Geumwang-eup
Target entity description: Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
  • A. Eumseong-eup
    Eumseong-eup is the main urban township and administrative center of Eumseong County in North Chungcheong Province, South Korea.
  • B. Gamgok-myeon
    Gamgok-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, South Korea.
  • C. Suyŏng-gu
    Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
  • D. Daedeok-gu
    Daedeok-gu is a district in the city of Daejeon, South Korea, known for encompassing parts of the country’s major research and science complex.
  • E. Seo-gu
    Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc2497ce881909b05eb9cec67d9e7 completed March 7, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea86ab4cc8190ba2203c09f72aaa6 completed March 9, 2026, 11 a.m.
NEDg Description generation batch_69aeaa6cb58081909a0897d4cb328063 completed March 9, 2026, 11:09 a.m.
NED2 Entity disambiguation (via description) batch_69aeabb6d43481908899080f6ca58101 completed March 9, 2026, 11:15 a.m.
Created at: March 4, 2026, 7:48 p.m.