Triple

T3532203
Position Surface form Disambiguated ID Type / Status
Subject Taras Shevchenko National University of Kyiv E74685 entity
Predicate shortName P43 FINISHED
Object 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.
 E366181 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: [Taras Shevchenko National University of Kyiv, shortName, KNU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KNU
Context triple: [Taras Shevchenko National University of Kyiv, shortName, KNU]
  • A. KNUQ
    KNUQ is the ICAO airport code for Moffett Federal Airfield, a joint civil-military airfield located in Moffett Field, California.
  • B. KNA
    KNA is the three-letter ISO 3166-1 alpha-3 country code assigned to Saint Kitts and Nevis.
  • C. KMTN
    KMTN is the ICAO airport code for Martin State Airport, a public airport located near Baltimore, Maryland, in the United States.
  • D. KU
    KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
  • E. 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.
  • 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: [Taras Shevchenko National University of Kyiv, shortName, KNU]
Generated description
KNU is a leading Ukrainian public research university located in Kyiv, widely regarded as one of the country’s most prestigious higher education institutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KNU
Target entity description: KNU is a leading Ukrainian public research university located in Kyiv, widely regarded as one of the country’s most prestigious higher education institutions.
  • A. KNUQ
    KNUQ is the ICAO airport code for Moffett Federal Airfield, a joint civil-military airfield located in Moffett Field, California.
  • B. KNA
    KNA is the three-letter ISO 3166-1 alpha-3 country code assigned to Saint Kitts and Nevis.
  • C. KMTN
    KMTN is the ICAO airport code for Martin State Airport, a public airport located near Baltimore, Maryland, in the United States.
  • D. KU
    KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
  • E. KU
    KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9a14c881908932b17ed3eececb completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e9a2b848190a5c2b3072fa6c44c completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37f07ab70819089fdb7083b81b992 completed March 13, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_69b38078bc288190b69d73a64acce8ca completed March 13, 2026, 3:11 a.m.
Created at: March 8, 2026, 3:19 p.m.