Triple

T11174715
Position Surface form Disambiguated ID Type / Status
Subject Maengdong-myeon E264379 entity
Predicate partOf P40 FINISHED
Object Eumseong County E276151 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: Eumseong County | Statement: [Maengdong-myeon, partOf, Eumseong County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eumseong County
Context triple: [Maengdong-myeon, partOf, Eumseong County]
  • A. Eumseong County chosen
    Eumseong County is a rural administrative region in North Chungcheong Province, South Korea, known as the birthplace of former UN Secretary-General Ban Ki-moon.
  • B. Uiseong County
    Uiseong County is a rural administrative region in southeastern South Korea known for its agricultural production and traditional Korean cultural heritage.
  • C. Seongju County
    Seongju County is a rural administrative region in southeastern South Korea known for its melon farming and traditional cultural heritage.
  • D. Dalseong County
    Dalseong County is a largely rural administrative district on the outskirts of Daegu in South Korea, known for its natural scenery, agricultural areas, and growing suburban developments.
  • E. Bonghwa County
    Bonghwa County is a rural administrative region in northeastern South Korea known for its mountainous landscapes, forests, and traditional cultural heritage.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e897774c819088ebc7231cebfba6 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69f01869e6c8819093f2768b57b183aa completed April 28, 2026, 2:16 a.m.
Created at: April 8, 2026, 9:29 p.m.