Triple

T4941996
Position Surface form Disambiguated ID Type / Status
Subject Interregional Academy of Personnel Management E110958 entity
Predicate alternativeName P39 FINISHED
Object MAUP
MAUP is a Ukrainian private higher education institution known for its programs in management, law, and social sciences.
 E481332 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: MAUP | Statement: [Interregional Academy of Personnel Management, alternativeName, MAUP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAUP
Context triple: [Interregional Academy of Personnel Management, alternativeName, MAUP]
  • A. MAU
    MAU (Media Access Unit) is a network device used in IEEE 802.5 Token Ring networks to connect multiple stations and manage the ring’s physical topology.
  • B. Ma$e
    Ma$e is an American rapper and songwriter known for his late-1990s success with Bad Boy Records and his smooth, laid-back delivery on hits like "Feel So Good."
  • C. Mau
    Mau is a city in the Purvanchal region of eastern Uttar Pradesh, India, known for its textile and power-loom industry.
  • D. Maasim
    Maasim is a coastal municipality in the province of South Cotabato on the island of Mindanao in the Philippines, known for agriculture and fishing.
  • E. Manyika
    Manyika is a major dialect of the Shona language spoken primarily in eastern Zimbabwe and adjacent areas of Mozambique.
  • 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: MAUP
Triple: [Interregional Academy of Personnel Management, alternativeName, MAUP]
Generated description
MAUP is a Ukrainian private higher education institution known for its programs in management, law, and social sciences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAUP
Target entity description: MAUP is a Ukrainian private higher education institution known for its programs in management, law, and social sciences.
  • A. MAU
    MAU (Media Access Unit) is a network device used in IEEE 802.5 Token Ring networks to connect multiple stations and manage the ring’s physical topology.
  • B. Ma$e
    Ma$e is an American rapper and songwriter known for his late-1990s success with Bad Boy Records and his smooth, laid-back delivery on hits like "Feel So Good."
  • C. Mau
    Mau is a city in the Purvanchal region of eastern Uttar Pradesh, India, known for its textile and power-loom industry.
  • D. Maasim
    Maasim is a coastal municipality in the province of South Cotabato on the island of Mindanao in the Philippines, known for agriculture and fishing.
  • E. Manyika
    Manyika is a major dialect of the Shona language spoken primarily in eastern Zimbabwe and adjacent areas of Mozambique.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70a5f56481908365d0fe16892bf4 completed March 20, 2026, 4:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77c19090819084f6b98d22c2b3a0 completed March 21, 2026, 10:49 a.m.
NEDg Description generation batch_69be79617a788190a2e7ae0a234002da completed March 21, 2026, 10:56 a.m.
NED2 Entity disambiguation (via description) batch_69be79ce18a48190a61880aaa00f02e0 completed March 21, 2026, 10:58 a.m.
Created at: March 20, 2026, 1:31 p.m.