Triple

T23216839
Position Surface form Disambiguated ID Type / Status
Subject Eunpyeong-gu E580767 entity
Predicate borderedBy P224 FINISHED
Object Yangju-si 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: Yangju-si | Statement: [Eunpyeong-gu, borderedBy, Yangju-si]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yangju-si
Context triple: [Eunpyeong-gu, borderedBy, Yangju-si]
  • A. Geumwang-eup
    Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
  • B. Yeonpyeong-myeon
    Yeonpyeong-myeon is an administrative township of Incheon, South Korea, that governs the Yeonpyeong Island group near the maritime border with North Korea.
  • C. Samseong-myeon
    Samseong-myeon is a rural township-level administrative area within Eumseong County in North Chungcheong Province, South Korea.
  • D. Ungchon-myeon
    Ungchon-myeon is a rural township-level administrative division located within Ulju County in Ulsan, South Korea.
  • E. Yangju chosen
    Yangju is a city in northwestern South Korea known for its mix of suburban residential areas, light industry, and proximity to Seoul.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f19165949c81908e4d66a8a2b0a25a completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.