Triple

T224249
Position Surface form Disambiguated ID Type / Status
Subject Busan E4279 entity
Predicate hasRailStation P726 FINISHED
Object Busan Station
Busan Station is a major railway hub in Busan, South Korea, serving high-speed KTX trains and regional services as one of the country’s key transportation centers.
 E36550 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: Busan Station | Statement: [Busan, hasRailStation, Busan Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Busan Station
Context triple: [Busan, hasRailStation, Busan Station]
  • A. Busan
    Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
  • B. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • C. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • D. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • E. Gwangju
    Gwangju is a major metropolitan city in southwestern South Korea known for its rich cultural heritage and pivotal role in the country’s pro-democracy movement.
  • 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: Busan Station
Triple: [Busan, hasRailStation, Busan Station]
Generated description
Busan Station is a major railway hub in Busan, South Korea, serving high-speed KTX trains and regional services as one of the country’s key transportation centers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Busan Station
Target entity description: Busan Station is a major railway hub in Busan, South Korea, serving high-speed KTX trains and regional services as one of the country’s key transportation centers.
  • A. Busan
    Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
  • B. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • C. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • D. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • E. Gwangju
    Gwangju is a major metropolitan city in southwestern South Korea known for its rich cultural heritage and pivotal role in the country’s pro-democracy movement.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c7194fc8190a2d02d446ae3a75e completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a399a2991c8190a3f79aa899720a7c completed March 1, 2026, 1:42 a.m.
NEDg Description generation batch_69a39afffa5c8190a71e91cbea794197 completed March 1, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_69a39b7aac5881908b2efeaae2603555 completed March 1, 2026, 1:50 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.