Triple

T6686571
Position Surface form Disambiguated ID Type / Status
Subject Daegu Gwangyeoksi E152111 entity
Predicate hasUniversity P113 FINISHED
Object Keimyung University E150180 NE FINISHED

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: Keimyung University | Statement: [Daegu Gwangyeoksi, hasUniversity, Keimyung University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keimyung University
Context triple: [Daegu Gwangyeoksi, hasUniversity, Keimyung University]
  • A. Keimyung University chosen
    Keimyung University is a private Christian university in Daegu, South Korea, known for its international programs and picturesque campus.
  • B. Sungkyul University
    Sungkyul University is a South Korean higher education institution known for producing alumni such as actor Wi Ha-joon.
  • C. Chosun University
    Chosun University is a major private research university in South Korea known for its comprehensive academic programs and regional influence.
  • D. Dongguk University
    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.
  • E. Incheon National University
    Incheon National University is a national public research university in Incheon, South Korea, known for its focus on global education and industry-academic cooperation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14cd6748190aad4badd5f253478 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a30754cc8190beeb97b48c167a15 completed March 28, 2026, 9:44 a.m.
Created at: March 27, 2026, 2:04 p.m.