Triple

T14371873
Position Surface form Disambiguated ID Type / Status
Subject Uiryeong County E356376 entity
Predicate capital P234 FINISHED
Object Uiryeong-eup E1095361 NE FINISHED

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: Uiryeong-eup | Statement: [Uiryeong County, capital, Uiryeong-eup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uiryeong-eup
Context triple: [Uiryeong County, capital, Uiryeong-eup]
  • A. Geumwang-eup
    Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
  • B. Eumseong-eup
    Eumseong-eup is the main urban township and administrative center of Eumseong County in North Chungcheong Province, South Korea.
  • C. Suyŏng-gu
    Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
  • D. Uiryeong-gun chosen
    Uiryeong-gun is a rural county in South Gyeongsang Province, South Korea, known for its agricultural landscape and small-town communities.
  • E. Geumjeong-gu
    Geumjeong-gu is a district in Busan, South Korea, known for its residential areas, transportation hubs, and proximity to Geumjeongsan Mountain.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fb2082c8190b42cc5f2bab4f574 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde16198488190ad69eeebd09c45da completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:15 a.m.