Triple

T16092310
Position Surface form Disambiguated ID Type / Status
Subject Dangjin E390386 entity
Predicate hangulName P17869 FINISHED
Object 당진시
당진시는 충청남도 서북부에 위치한 산업·항만 도시로, 현대제철 당진제철소와 당진항 등을 중심으로 한 중공업과 물류 산업이 발달한 기초자치단체이다.
E1194836 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: 당진시 | Statement: [Dangjin, hangulName, 당진시]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 당진시
Context triple: [Dangjin, hangulName, 당진시]
  • A. Gijang County
    Gijang County is a coastal administrative region in northeastern Busan, South Korea, known for its scenic shoreline, seafood, and growing residential and tourist areas.
  • B. Sacheon
    Sacheon is a coastal city in South Gyeongsang Province, South Korea, known for its fishing industry, maritime transport, and aerospace manufacturing.
  • C. Gunpo
    Gunpo is a small satellite city in South Korea’s Seoul Capital Area, known for its residential communities and convenient commuter access to Seoul.
  • D. Hwaseong-si
    Hwaseong-si is a rapidly growing city in Gyeonggi Province, South Korea, known for its industrial complexes, coastal wetlands, and proximity to Seoul.
  • E. 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.
  • 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: 당진시
Triple: [Dangjin, hangulName, 당진시]
Generated description
당진시는 충청남도 서북부에 위치한 산업·항만 도시로, 현대제철 당진제철소와 당진항 등을 중심으로 한 중공업과 물류 산업이 발달한 기초자치단체이다.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 당진시
Target entity description: 당진시는 충청남도 서북부에 위치한 산업·항만 도시로, 현대제철 당진제철소와 당진항 등을 중심으로 한 중공업과 물류 산업이 발달한 기초자치단체이다.
  • A. Gijang County
    Gijang County is a coastal administrative region in northeastern Busan, South Korea, known for its scenic shoreline, seafood, and growing residential and tourist areas.
  • B. Sacheon
    Sacheon is a coastal city in South Gyeongsang Province, South Korea, known for its fishing industry, maritime transport, and aerospace manufacturing.
  • C. Gunpo
    Gunpo is a small satellite city in South Korea’s Seoul Capital Area, known for its residential communities and convenient commuter access to Seoul.
  • D. Hwaseong-si
    Hwaseong-si is a rapidly growing city in Gyeonggi Province, South Korea, known for its industrial complexes, coastal wetlands, and proximity to Seoul.
  • E. 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.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1858d1264819099434d7201614d05 completed April 17, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb9550f0819092660f6c4b0d708e completed May 10, 2026, 2:21 a.m.
NEDg Description generation batch_69ffed526eac8190968a19738ab019e7 completed May 10, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69ffedda25fc8190b9eef3e7752f95f5 completed May 10, 2026, 2:30 a.m.
Created at: April 10, 2026, 4:59 a.m.