Triple

T7376803
Position Surface form Disambiguated ID Type / Status
Subject University of Ulsan E170145 entity
Predicate nativeName P15 FINISHED
Object 울산대학교 E170145 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: 울산대학교 | Statement: [University of Ulsan, nativeName, 울산대학교]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 울산대학교
Context triple: [University of Ulsan, nativeName, 울산대학교]
  • A. University of Ulsan chosen
    The University of Ulsan is a major private research university in Ulsan, South Korea, known for its strong engineering and industrial cooperation programs.
  • B. 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.
  • C. Sungkyul University
    Sungkyul University is a South Korean higher education institution known for producing alumni such as actor Wi Ha-joon.
  • D. Daegu University
    Daegu University is a South Korean higher education institution known for its comprehensive academic programs and strong emphasis on social welfare and special education.
  • E. Pusan National University
    Pusan National University is a major national research university in South Korea known for its comprehensive academic programs and strong regional influence in the city of Busan.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1a8b18c8190ad1a19521eda2319 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c941f469c881908e83cfd6c8191af1 completed March 29, 2026, 3:15 p.m.
Created at: March 27, 2026, 3:07 p.m.