Triple

T18159802
Position Surface form Disambiguated ID Type / Status
Subject Pocheon E434726 entity
Predicate borderedBy P224 FINISHED
Object Gapyeong County 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: Gapyeong County | Statement: [Pocheon, borderedBy, Gapyeong County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gapyeong County
Context triple: [Pocheon, borderedBy, Gapyeong County]
  • A. Gapyeong County chosen
    Gapyeong County is a rural county in Gyeonggi Province, South Korea, known for its scenic mountains, rivers, and historical sites from the Korean War.
  • B. Jincheon County
    Jincheon County is a rural administrative region in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
  • C. Uiseong County
    Uiseong County is a rural administrative region in southeastern South Korea known for its agricultural production and traditional Korean cultural heritage.
  • D. Bonghwa County
    Bonghwa County is a rural administrative region in northeastern South Korea known for its mountainous landscapes, forests, and traditional cultural heritage.
  • E. Goryeong County
    Goryeong County is a rural administrative region in southeastern South Korea known for its historical sites and agricultural landscape.
  • 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dec0e0388190af11ac167411da96 completed April 19, 2026, 1:55 p.m.
Created at: April 10, 2026, 10:30 a.m.