Triple

T19089361
Position Surface form Disambiguated ID Type / Status
Subject Chun Doo-hwan E467239 entity
Predicate birthPlace P1 FINISHED
Object Hapcheon 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: Hapcheon County | Statement: [Chun Doo-hwan, birthPlace, Hapcheon County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hapcheon County
Context triple: [Chun Doo-hwan, birthPlace, Hapcheon County]
  • A. Hapcheon County chosen
    Hapcheon County is a rural administrative region in South Gyeongsang Province, South Korea, known for its scenic landscapes and cultural heritage sites.
  • B. Gijang County
    Gijang County is a coastal administrative region in northeastern Busan, South Korea, known for its scenic shoreline, seafood, and growing residential and tourist areas.
  • C. Bonghwa County
    Bonghwa County is a rural administrative region in northeastern South Korea known for its mountainous landscapes, forests, and traditional cultural heritage.
  • D. Seocheon County
    Seocheon County is a coastal administrative region in South Chungcheong Province, South Korea, known for its tidal flats, fishing industry, and ecological wetlands.
  • E. Hongseong County
    Hongseong County is a county in South Chungcheong Province, South Korea, known as the provincial capital and an administrative and cultural center of the region.
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e34981648190a89b006831846940 completed April 20, 2026, 8:26 a.m.
Created at: April 10, 2026, 12:04 p.m.