Triple

T13217716
Position Surface form Disambiguated ID Type / Status
Subject 연제구 E314662 entity
Predicate hasNotablePlace P10233 FINISHED
Object 연산역
연산역은 부산광역시 연제구에 위치한 도시철도 1·3호선 환승역으로, 지역 교통의 중심 역할을 하는 지하철역이다.
E1028387 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: 연산역 | Statement: [연제구, hasNotablePlace, 연산역]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 연산역
Context triple: [연제구, hasNotablePlace, 연산역]
  • A. Nakseonjae Complex
    Nakseonjae Complex is a refined residential compound within Seoul’s Changdeokgung Palace, known for its elegant Joseon-era architecture and use as royal living quarters.
  • B. Tongil Station
    Tongil Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
  • C. Gwanaksan
    Gwanaksan is a prominent mountain in the Seoul metropolitan area of South Korea, known for its hiking trails, rocky peaks, and scenic views over the surrounding cities.
  • D. Askim Station
    Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
  • E. Samhung Station
    Samhung Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
  • 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: 연산역
Triple: [연제구, hasNotablePlace, 연산역]
Generated description
연산역은 부산광역시 연제구에 위치한 도시철도 1·3호선 환승역으로, 지역 교통의 중심 역할을 하는 지하철역이다.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 연산역
Target entity description: 연산역은 부산광역시 연제구에 위치한 도시철도 1·3호선 환승역으로, 지역 교통의 중심 역할을 하는 지하철역이다.
  • A. Nakseonjae Complex
    Nakseonjae Complex is a refined residential compound within Seoul’s Changdeokgung Palace, known for its elegant Joseon-era architecture and use as royal living quarters.
  • B. Tongil Station
    Tongil Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
  • C. Gwanaksan
    Gwanaksan is a prominent mountain in the Seoul metropolitan area of South Korea, known for its hiking trails, rocky peaks, and scenic views over the surrounding cities.
  • D. Askim Station
    Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
  • E. Samhung Station
    Samhung Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf392e08190949ee4d194566395 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2085f88190be8cfc309d21f9cb completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f7036009808190aea595cd542e0cf1 completed May 3, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_69f7040e32a4819083a9f4efe96fd9ca completed May 3, 2026, 8:15 a.m.
Created at: April 9, 2026, 9:18 p.m.