Triple

T16685366
Position Surface form Disambiguated ID Type / Status
Subject Cho Yeo-jeong E405448 entity
Predicate almaMater P5 FINISHED
Object Dongguk University 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: Dongguk University | Statement: [Cho Yeo-jeong, almaMater, Dongguk University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dongguk University
Context triple: [Cho Yeo-jeong, almaMater, Dongguk University]
  • A. Dongguk University chosen
    Dongguk University is a prominent private university in South Korea known for its Buddhist foundation and strong programs in the humanities, arts, and social sciences.
  • B. Dong-A University
    Dong-A University is a major private research university in Busan, South Korea, known for its comprehensive academic programs and multiple urban campuses.
  • C. Chosun University
    Chosun University is a major private research university in South Korea known for its comprehensive academic programs and regional influence.
  • D. Hansung University
    Hansung University is a private higher education institution in Seoul, South Korea, known for its programs in humanities, social sciences, design, and information technology.
  • E. Kyonggi University
    Kyonggi University is a private South Korean university known for its main campus in Suwon and a broad range of undergraduate and graduate programs.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea550c0819085bd36c44237a61a completed April 18, 2026, 12:52 p.m.
Created at: April 10, 2026, 5:19 a.m.