Triple

T20258029
Position Surface form Disambiguated ID Type / Status
Subject South Chungcheong Province E498754 entity
Predicate hasMajorCity P316 FINISHED
Object Dangjin 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: Dangjin | Statement: [South Chungcheong Province, hasMajorCity, Dangjin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dangjin
Context triple: [South Chungcheong Province, hasMajorCity, Dangjin]
  • A. Dangjin chosen
    Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
  • B. Tancheon
    Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
  • C. Kyongsong
    Kyongsong is a coastal town and county-level city in northeastern North Korea known for its hot springs and location along the Sea of Japan (East Sea).
  • D. Kŏje-si
    Kŏje-si is the McCune–Reischauer romanization of Geoje, a city in South Gyeongsang Province, South Korea, known for its shipbuilding industry and scenic coastal landscapes.
  • E. Icheon
    Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
  • 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e674c7296c819092860942de8f28d5 completed April 20, 2026, 6:47 p.m.
Created at: April 11, 2026, 11:41 p.m.