Triple

T2013673
Position Surface form Disambiguated ID Type / Status
Subject Gyeonggi Province E43744 entity
Predicate hasCity P316 FINISHED
Object Uiwang
Uiwang is a small inland city in South Korea known for its transportation infrastructure and proximity to Seoul.
 E226750 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: Uiwang | Statement: [Gyeonggi Province, hasCity, Uiwang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Uiwang
Context triple: [Gyeonggi Province, hasCity, Uiwang]
  • A. Pyeongtaek
    Pyeongtaek is a South Korean city in Gyeonggi Province known for its major U.S. and UN military presence, including large bases such as Camp Humphreys.
  • B. Gapcheon
    Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
  • C. 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.
  • D. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • E. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • 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: Uiwang
Triple: [Gyeonggi Province, hasCity, Uiwang]
Generated description
Uiwang is a small inland city in South Korea known for its transportation infrastructure and proximity to Seoul.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Uiwang
Target entity description: Uiwang is a small inland city in South Korea known for its transportation infrastructure and proximity to Seoul.
  • A. Pyeongtaek
    Pyeongtaek is a South Korean city in Gyeonggi Province known for its major U.S. and UN military presence, including large bases such as Camp Humphreys.
  • B. Gapcheon
    Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
  • C. 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.
  • D. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • E. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8b42d508190bf2b63132bb2ad77 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0aea65d881908eb751349a2c23f9 completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0bac5c448190997e58297355f3d6 completed March 8, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_69ae0c31f00c8190bb29098f95ee4cb9 completed March 8, 2026, 11:54 p.m.
Created at: March 4, 2026, 7:37 p.m.