Triple

T7263670
Position Surface form Disambiguated ID Type / Status
Subject Yangsan E159717 entity
Predicate hasKoreanName P17869 FINISHED
Object 양산시
양산시는 대한민국 경상남도에 위치한 도시로, 부산과 울산 인근의 베드타운이자 산업·주거 기능이 결합된 중견 도시이다.
 E652463 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: 양산시 | Statement: [Yangsan, hasKoreanName, 양산시]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 양산시
Context triple: [Yangsan, hasKoreanName, 양산시]
  • A. 밀양시
    밀양시는 경상남도 동북부에 위치한 시로, 낙동강과 밀양강이 합류하는 분지 지형과 밀양아리랑, 얼음골 등으로 유명한 도시이다.
  • B. Kurseong
    Kurseong is a small hill town in the Darjeeling district of northern West Bengal, India, known for its tea gardens, cool climate, and views of the Eastern Himalayas.
  • C. Suncheon
    Suncheon is a city in South Jeolla Province, South Korea, known for its ecological attractions such as the Suncheon Bay Wetland Reserve and its role as a regional administrative and cultural center.
  • D. Icheon
    Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
  • E. Nam-gu, Busan
    Nam-gu, Busan is a coastal district in the south-central part of Busan, South Korea, known for its residential neighborhoods, universities, and views over the city and harbor.
  • 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: 양산시
Triple: [Yangsan, hasKoreanName, 양산시]
Generated description
양산시는 대한민국 경상남도에 위치한 도시로, 부산과 울산 인근의 베드타운이자 산업·주거 기능이 결합된 중견 도시이다.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 양산시
Target entity description: 양산시는 대한민국 경상남도에 위치한 도시로, 부산과 울산 인근의 베드타운이자 산업·주거 기능이 결합된 중견 도시이다.
  • A. 밀양시
    밀양시는 경상남도 동북부에 위치한 시로, 낙동강과 밀양강이 합류하는 분지 지형과 밀양아리랑, 얼음골 등으로 유명한 도시이다.
  • B. Kurseong
    Kurseong is a small hill town in the Darjeeling district of northern West Bengal, India, known for its tea gardens, cool climate, and views of the Eastern Himalayas.
  • C. Suncheon
    Suncheon is a city in South Jeolla Province, South Korea, known for its ecological attractions such as the Suncheon Bay Wetland Reserve and its role as a regional administrative and cultural center.
  • D. Icheon
    Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
  • E. Nam-gu, Busan
    Nam-gu, Busan is a coastal district in the south-central part of Busan, South Korea, known for its residential neighborhoods, universities, and views over the city and harbor.
  • 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac9fab88190881ab9e1cd94cdc1 completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3c7754481908ff7cc0fc6419599 completed March 28, 2026, 1:12 p.m.
NEDg Description generation batch_69c7d5c7c3a48190b8d1b5e351ebfbd5 completed March 28, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_69c7d639f7f08190a360bd2899e6fef8 completed March 28, 2026, 1:23 p.m.
Created at: March 27, 2026, 2:57 p.m.