Triple

T8980900
Position Surface form Disambiguated ID Type / Status
Subject 금정구 E214521 entity
Predicate hasMountain P10602 FINISHED
Object 금정산
금정산은 부산광역시 북부에 위치한 산으로, 금정구 일대를 포함하며 산성·사찰·등산로로 유명한 대표적인 도심 근교 명산이다.
 E769257 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: 금정산 | Statement: [금정구, hasMountain, 금정산]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 금정산
Context triple: [금정구, hasMountain, 금정산]
  • A. 금정구
    금정구는 부산광역시 북동부에 위치한 행정구로, 금정산과 범어사 등 자연·문화 유산이 풍부한 주거·교육 중심 지역이다.
  • B. Kyeyang-ku
    Kyeyang-ku is an administrative district in Incheon, South Korea, known for its mix of residential areas, historical sites, and access to natural attractions like Gyeyang Mountain.
  • C. Cheongnyang-eup
    Cheongnyang-eup is a town-level administrative division located within Ulju County in Ulsan, South Korea.
  • 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. Sasang-gu
    Sasang-gu is an administrative district in Busan, South Korea, known for its transportation hubs, industrial areas, and mixed residential-commercial neighborhoods.
  • 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: 금정산
Triple: [금정구, hasMountain, 금정산]
Generated description
금정산은 부산광역시 북부에 위치한 산으로, 금정구 일대를 포함하며 산성·사찰·등산로로 유명한 대표적인 도심 근교 명산이다.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 금정산
Target entity description: 금정산은 부산광역시 북부에 위치한 산으로, 금정구 일대를 포함하며 산성·사찰·등산로로 유명한 대표적인 도심 근교 명산이다.
  • A. 금정구
    금정구는 부산광역시 북동부에 위치한 행정구로, 금정산과 범어사 등 자연·문화 유산이 풍부한 주거·교육 중심 지역이다.
  • B. Kyeyang-ku
    Kyeyang-ku is an administrative district in Incheon, South Korea, known for its mix of residential areas, historical sites, and access to natural attractions like Gyeyang Mountain.
  • C. Cheongnyang-eup
    Cheongnyang-eup is a town-level administrative division located within Ulju County in Ulsan, South Korea.
  • 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. Sasang-gu
    Sasang-gu is an administrative district in Busan, South Korea, known for its transportation hubs, industrial areas, and mixed residential-commercial neighborhoods.
  • 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_69ca839ea8b88190922c6a326ffcc0d3 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc67a76f748190a4abad5d53d58fa8 completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc974f0f8819085c63deb53b95b80 completed April 3, 2026, 2:06 p.m.
NEDg Description generation batch_69cfca11f7b8819082ea5c74f700cf4b completed April 3, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_69cfca735c50819088c2805c62d96d62 completed April 3, 2026, 2:10 p.m.
Created at: March 30, 2026, 7:03 p.m.