Triple

T20669751
Position Surface form Disambiguated ID Type / Status
Subject 진주 E507987 entity
Predicate hasUniversity P113 FINISHED
Object Jinju Health College 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: Jinju Health College | Statement: [진주, hasUniversity, Jinju Health College]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jinju Health College
Context triple: [진주, hasUniversity, Jinju Health College]
  • A. Jinju Health College chosen
    Jinju Health College is a specialized higher education institution in Jinju, South Korea, focused on training professionals in health and medical-related fields.
  • B. Kyungsung University
    Kyungsung University is a private higher education institution located in Busan, South Korea, known for its programs in humanities, social sciences, arts, and media.
  • C. Yeoju University
    Yeoju University is a higher education institution located in Yeoju, South Korea, offering a range of undergraduate and specialized programs.
  • D. Soonchunhyang University
    Soonchunhyang University is a private South Korean university known for its strong medical and health sciences programs and comprehensive undergraduate and graduate offerings.
  • E. Hallym University
    Hallym University is a private research university in South Korea known for its strong programs in medicine, humanities, and social sciences.
  • 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c735048190a01cb7692928d66e completed April 20, 2026, 11:24 p.m.
Created at: April 16, 2026, 11:44 a.m.