Triple

T15924693
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Internal Affairs of Serbia E386177 entity
Predicate abbreviation P43 FINISHED
Object MUP
MUP is the commonly used abbreviation for Serbia’s Ministry of Internal Affairs, the government body responsible for police, security, and internal administrative affairs.
E1185302 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: MUP | Statement: [Ministry of Internal Affairs of Serbia, abbreviation, MUP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MUP
Context triple: [Ministry of Internal Affairs of Serbia, abbreviation, MUP]
  • A. MUF
    MUF is the youth wing of Sweden's Moderate Party, engaging young people in center-right politics and policy issues.
  • B. MUH
    MUH is the IATA airport code for Marsa Matruh International Airport, which serves the coastal city of Mersa Matruh in Egypt.
  • C. MPS
    MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
  • D. MPS
    MPS (Metal Performance Shaders) is an Apple framework that provides highly optimized GPU-accelerated compute and graphics shaders for tasks like image processing and machine learning on Apple devices.
  • E. MPS
    MPS is the central government agency responsible for public security, policing, and domestic law enforcement in the People's Republic of China.
  • 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: MUP
Triple: [Ministry of Internal Affairs of Serbia, abbreviation, MUP]
Generated description
MUP is the commonly used abbreviation for Serbia’s Ministry of Internal Affairs, the government body responsible for police, security, and internal administrative affairs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MUP
Target entity description: MUP is the commonly used abbreviation for Serbia’s Ministry of Internal Affairs, the government body responsible for police, security, and internal administrative affairs.
  • A. MUF
    MUF is the youth wing of Sweden's Moderate Party, engaging young people in center-right politics and policy issues.
  • B. MUH
    MUH is the IATA airport code for Marsa Matruh International Airport, which serves the coastal city of Mersa Matruh in Egypt.
  • C. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • D. MPS
    MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
  • E. MPS
    MPS (Metal Performance Shaders) is an Apple framework that provides highly optimized GPU-accelerated compute and graphics shaders for tasks like image processing and machine learning on Apple devices.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1568424f08190bffe6ee465a0db9a completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5adcde88190ae2a845aaa9d31ac completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb6c4a66c8190bba70da71c9ec576 completed May 9, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7a373d88190a2fcf75022f3e161 completed May 9, 2026, 10:39 p.m.
Created at: April 10, 2026, 4:52 a.m.