Triple

T21509924
Position Surface form Disambiguated ID Type / Status
Subject South Pyongan Province E530687 entity
Predicate hasCounty P285 FINISHED
Object Chongnam 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: Chongnam County | Statement: [South Pyongan Province, hasCounty, Chongnam County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chongnam County
Context triple: [South Pyongan Province, hasCounty, Chongnam County]
  • A. Bonghwa County
    Bonghwa County is a rural administrative region in northeastern South Korea known for its mountainous landscapes, forests, and traditional cultural heritage.
  • B. Yeoncheon County
    Yeoncheon County is a rural county in Gyeonggi Province, South Korea, known for its location near the Demilitarized Zone (DMZ) and its historical military significance.
  • C. Cheongsong County
    Cheongsong County is a rural county in eastern South Korea known for its scenic mountains, apple orchards, and traditional cultural heritage.
  • D. Yongwon County chosen
    Yongwon County is an administrative county located within South Pyongan Province in central North Korea.
  • E. Cheongwon County
    Cheongwon County was a former administrative county in North Chungcheong Province, South Korea, that surrounded the city of Cheongju before being incorporated into it.
  • 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:25 p.m.