Triple

T9876263
Position Surface form Disambiguated ID Type / Status
Subject Masaryk University E240079 entity
Predicate hasAbbreviation P43 FINISHED
Object MU
MU is the common abbreviation for Masaryk University, a major public research university located in Brno, Czech Republic.
 E826491 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: MU | Statement: [Masaryk University, hasAbbreviation, MU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MU
Context triple: [Masaryk University, hasAbbreviation, MU]
  • A. MU
    MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
  • B. MU
    MU is the commonly used abbreviation for the University of Missouri, a major public research university based in Columbia, Missouri.
  • C. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • D. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • E. UM
    UM is a public research university in Oxford, Mississippi, commonly known as "Ole Miss" and recognized for its academic programs and SEC 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: MU
Triple: [Masaryk University, hasAbbreviation, MU]
Generated description
MU is the common abbreviation for Masaryk University, a major public research university located in Brno, Czech Republic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MU
Target entity description: MU is the common abbreviation for Masaryk University, a major public research university located in Brno, Czech Republic.
  • A. MU
    MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
  • B. MU
    MU is the commonly used abbreviation for the University of Missouri, a major public research university based in Columbia, Missouri.
  • C. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • D. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • E. UM
    UM is a public research university in Oxford, Mississippi, commonly known as "Ole Miss" and recognized for its academic programs and SEC 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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3fb58d481908407898912c4b4e9 completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e47b62388190a033743376500375 completed April 5, 2026, 4:26 a.m.
NEDg Description generation batch_69d1e5d0da7081908e14fe4bc6623ea5 completed April 5, 2026, 4:32 a.m.
NED2 Entity disambiguation (via description) batch_69d1e6af89f88190abe63f8172182f58 completed April 5, 2026, 4:35 a.m.
Created at: March 30, 2026, 8:37 p.m.