Triple

T3510063
Position Surface form Disambiguated ID Type / Status
Subject Osan, South Korea E74173 entity
Predicate hangulName P17869 FINISHED
Object 오산시
오산시 is a city in Gyeonggi Province, South Korea, known as a suburban industrial and residential area located south of Seoul.
 E363256 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: 오산시 | Statement: [Osan, South Korea, hangulName, 오산시]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 오산시
Context triple: [Osan, South Korea, hangulName, 오산시]
  • A. Pyeongtaek
    Pyeongtaek is a South Korean city in Gyeonggi Province known for its major U.S. and UN military presence, including large bases such as Camp Humphreys.
  • B. Suseong District
    Suseong District is an affluent residential and commercial area in southeastern Daegu, South Korea, known for its high-quality schools, parks, and cultural amenities.
  • C. Jincheon County
    Jincheon County is a rural administrative region in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
  • D. 연제구
    연제구는 대한민국 부산광역시 중앙부에 위치한 행정구로, 주거·상업·행정 기능이 조화를 이루는 도심 지역이다.
  • E. Ganghwa County
    Ganghwa County is a rural island county in northwestern South Korea known for its historical sites, fortresses, and strategic location near the border with North Korea.
  • 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: 오산시
Triple: [Osan, South Korea, hangulName, 오산시]
Generated description
오산시 is a city in Gyeonggi Province, South Korea, known as a suburban industrial and residential area located south of Seoul.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 오산시
Target entity description: 오산시 is a city in Gyeonggi Province, South Korea, known as a suburban industrial and residential area located south of Seoul.
  • A. Pyeongtaek
    Pyeongtaek is a South Korean city in Gyeonggi Province known for its major U.S. and UN military presence, including large bases such as Camp Humphreys.
  • B. Suseong District
    Suseong District is an affluent residential and commercial area in southeastern Daegu, South Korea, known for its high-quality schools, parks, and cultural amenities.
  • C. Jincheon County
    Jincheon County is a rural administrative region in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
  • D. 연제구
    연제구는 대한민국 부산광역시 중앙부에 위치한 행정구로, 주거·상업·행정 기능이 조화를 이루는 도심 지역이다.
  • E. Ganghwa County
    Ganghwa County is a rural island county in northwestern South Korea known for its historical sites, fortresses, and strategic location near the border with North Korea.
  • 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc0e1f0c8190b054d9fba16ce4b3 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373e71ae8819096ea39955c92076a completed March 13, 2026, 2:18 a.m.
NEDg Description generation batch_69b374e50a088190ad4dc101efd68d54 completed March 13, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_69b37544b04c819090e6f59babd8017e completed March 13, 2026, 2:24 a.m.
Created at: March 8, 2026, 3:18 p.m.