Triple

T16815132
Position Surface form Disambiguated ID Type / Status
Subject Seongnam E408723 entity
Predicate hasRiver P165 FINISHED
Object Tancheon
Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
 E1242372 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: Tancheon | Statement: [Seongnam, hasRiver, Tancheon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tancheon
Context triple: [Seongnam, hasRiver, Tancheon]
  • A. Dangjin
    Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
  • B. Gwangmyeong
    Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
  • C. Hanseong
    Hanseong was the historical name for Seoul when it served as the capital of the Joseon Dynasty in Korea.
  • D. Sinchon
    Sinchon is a vibrant university district in Seoul, South Korea, known for its dense concentration of colleges, youth culture, shopping, and nightlife.
  • E. Gimcheon
    Gimcheon is a city in North Gyeongsang Province, South Korea, known as a regional transportation hub and administrative center.
  • 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: Tancheon
Triple: [Seongnam, hasRiver, Tancheon]
Generated description
Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tancheon
Target entity description: Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
  • A. Dangjin
    Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
  • B. Gwangmyeong
    Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
  • C. Hanseong
    Hanseong was the historical name for Seoul when it served as the capital of the Joseon Dynasty in Korea.
  • D. Sinchon
    Sinchon is a vibrant university district in Seoul, South Korea, known for its dense concentration of colleges, youth culture, shopping, and nightlife.
  • E. Gimcheon
    Gimcheon is a city in North Gyeongsang Province, South Korea, known as a regional transportation hub and administrative center.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e0e05081908bd5eaa64abe133d completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d45013048190a8073f34820ca85a completed May 10, 2026, 6:54 p.m.
NEDg Description generation batch_6a00d51835c48190b1a37de6ac25ceaa completed May 10, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_6a00d59b96108190a0e55f01529a0b64 completed May 10, 2026, 6:59 p.m.
Created at: April 10, 2026, 5:23 a.m.