Triple

T2685782
Position Surface form Disambiguated ID Type / Status
Subject Korea University E57481 entity
Predicate shortName P43 FINISHED
Object KU
KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
 E288843 NE FINISHED

How this triple was built (4 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: KU | Statement: [Korea University, shortName, KU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KU
Context triple: [Korea University, shortName, KU]
  • A. KU
    KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
  • B. KU
    KU is the commonly used abbreviation for Kettering University, a private university in Flint, Michigan known for its strong engineering and cooperative education programs.
  • C. KU
    KU is the vehicle registration code assigned to the district of Kulmbach in the Upper Franconia region of Bavaria, Germany.
  • D. UofK
    UofK is the commonly used abbreviation for the University of Khartoum, Sudan’s oldest and most prestigious public university.
  • E. Kansas State University
    Kansas State University is a public land-grant research university in Manhattan, Kansas, known for its strong programs in agriculture, engineering, and veterinary medicine and its prominent NCAA Division I athletics.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KU
Triple: [Korea University, shortName, KU]
Generated description
KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KU
Target entity description: KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
  • A. KU
    KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
  • B. KU
    KU is the commonly used abbreviation for Kettering University, a private university in Flint, Michigan known for its strong engineering and cooperative education programs.
  • C. KU
    KU is the vehicle registration code assigned to the district of Kulmbach in the Upper Franconia region of Bavaria, Germany.
  • D. UofK
    UofK is the commonly used abbreviation for the University of Khartoum, Sudan’s oldest and most prestigious public university.
  • E. Kansas State University
    Kansas State University is a public land-grant research university in Manhattan, Kansas, known for its strong programs in agriculture, engineering, and veterinary medicine and its prominent NCAA Division I athletics.
  • F. None of above. chosen

Provenance (5 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9ef2fe0819082bbe746ca682a7e completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa07228088190bb4942b3a25c938b completed March 10, 2026, 4:39 a.m.
NEDg Description generation batch_69afa0fef4c481908db42628cd6e72fe completed March 10, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_69afa1ffbc4881909bb326a8a2f2a05e completed March 10, 2026, 4:45 a.m.
Created at: March 6, 2026, 9:54 p.m.