Triple

T17469637
Position Surface form Disambiguated ID Type / Status
Subject Siheung E425371 entity
Predicate isPartOf P10 FINISHED
Object Sudogwon region NE NERFINISHED

How this triple was built (2 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: Sudogwon region | Statement: [Siheung, isPartOf, Sudogwon region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sudogwon region
Context triple: [Siheung, isPartOf, Sudogwon region]
  • A. Sudogwon region chosen
    The Sudogwon region is the densely populated metropolitan area surrounding Seoul in northwestern South Korea, encompassing the capital and its major satellite cities.
  • B. Yeongseo region
    The Yeongseo region is a western inland area of Gangwon Province in South Korea, known for its mountainous terrain and distinct local culture.
  • C. Honam region
    The Honam region is a southwestern area of South Korea traditionally encompassing the provinces of Jeolla and the city of Gwangju, known for its rich agriculture, distinct culture, and strong democratic activism.
  • D. Yeongdong region
    The Yeongdong region is an area on the eastern side of the Korean Peninsula, particularly in Gangwon Province, known for its coastal geography and distinct local culture.
  • E. Minho region
    The Minho region is a historic and culturally rich area in northwest Portugal, known for its lush green landscapes, traditional cuisine, and production of Vinho Verde wine.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451aad4a08190be7e25841da8e952 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.