Triple

T6616434
Position Surface form Disambiguated ID Type / Status
Subject Kyungpook National University E149362 entity
Predicate shortName P43 FINISHED
Object KNU
KNU is a major national research university in Daegu, South Korea, known for its comprehensive academic programs and strong emphasis on science and technology.
 E599854 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: KNU | Statement: [Kyungpook National University, shortName, KNU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KNU
Context triple: [Kyungpook National University, shortName, KNU]
  • A. KNU
    KNU is a leading Ukrainian public research university located in Kyiv, widely regarded as one of the country’s most prestigious higher education institutions.
  • B. KNU
    KNU is the IATA airport code assigned to Kanpur Airport in Kanpur, India.
  • C. KNUQ
    KNUQ is the ICAO airport code for Moffett Federal Airfield, a joint civil-military airfield located in Moffett Field, California.
  • D. KNO
    KNO is the IATA airport code for Kualanamu International Airport serving Medan and the surrounding region in North Sumatra, Indonesia.
  • E. KNTU
    KNTU is the ICAO airport code for Naval Air Station Oceana, a major United States Navy jet base located in Virginia Beach, Virginia.
  • 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: KNU
Triple: [Kyungpook National University, shortName, KNU]
Generated description
KNU is a major national research university in Daegu, South Korea, known for its comprehensive academic programs and strong emphasis on science and technology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KNU
Target entity description: KNU is a major national research university in Daegu, South Korea, known for its comprehensive academic programs and strong emphasis on science and technology.
  • A. KNU
    KNU is a leading Ukrainian public research university located in Kyiv, widely regarded as one of the country’s most prestigious higher education institutions.
  • B. KNU
    KNU is the IATA airport code assigned to Kanpur Airport in Kanpur, India.
  • C. KNUQ
    KNUQ is the ICAO airport code for Moffett Federal Airfield, a joint civil-military airfield located in Moffett Field, California.
  • D. KNO
    KNO is the IATA airport code for Kualanamu International Airport serving Medan and the surrounding region in North Sumatra, Indonesia.
  • E. KNTU
    KNTU is the ICAO airport code for Naval Air Station Oceana, a major United States Navy jet base located in Virginia Beach, Virginia.
  • 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_69c687ebc680819094caf71faba2efe2 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af57fd748190bb64f1965bab319f completed March 27, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbda469481908173db345ba2f216 completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd428b988190b01311ca02f4dff3 completed March 27, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_69c6cdcc10c08190aa98212bd17063a3 completed March 27, 2026, 6:34 p.m.
Created at: March 27, 2026, 1:57 p.m.