Triple

T16669125
Position Surface form Disambiguated ID Type / Status
Subject Moscow Aviation Institute E405058 entity
Predicate alternativeName P39 FINISHED
Object MAI
MAI is a prominent Russian university specializing in aerospace engineering, aviation, and related high-technology fields.
 E1227783 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: MAI | Statement: [Moscow Aviation Institute, alternativeName, MAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAI
Context triple: [Moscow Aviation Institute, alternativeName, MAI]
  • A. MAI
    MAI is the commonly used abbreviation for Romania’s Ministry of Internal Affairs, the government body responsible for internal security, public order, and civil administration.
  • B. MAI
    MAI is the National Rail station code for Maidenhead railway station in Berkshire, England.
  • C. MAI
    MAI is the commonly used acronym for Portugal’s Ministry of Internal Administration, the government body responsible for internal security, civil protection, and administrative affairs.
  • D. Mai-Mine
    Mai-Mine is a town in southern Eritrea known primarily for its agricultural activities and role as a local administrative center.
  • E. 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."
  • 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: MAI
Triple: [Moscow Aviation Institute, alternativeName, MAI]
Generated description
MAI is a prominent Russian university specializing in aerospace engineering, aviation, and related high-technology fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAI
Target entity description: MAI is a prominent Russian university specializing in aerospace engineering, aviation, and related high-technology fields.
  • A. MAI
    MAI is the commonly used abbreviation for Romania’s Ministry of Internal Affairs, the government body responsible for internal security, public order, and civil administration.
  • B. MAI
    MAI is the National Rail station code for Maidenhead railway station in Berkshire, England.
  • C. MAI
    MAI is the commonly used acronym for Portugal’s Ministry of Internal Administration, the government body responsible for internal security, civil protection, and administrative affairs.
  • D. Mai-Mine
    Mai-Mine is a town in southern Eritrea known primarily for its agricultural activities and role as a local administrative center.
  • E. 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."
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37c9fa3d081909457b1bdea1d96e0 completed April 18, 2026, 12:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a34852c81908c00ff8e36923cee completed May 10, 2026, 1:37 p.m.
NEDg Description generation batch_6a008abfcb4481908efb8a1cb3c0086e completed May 10, 2026, 1:40 p.m.
NED2 Entity disambiguation (via description) batch_6a008b55b28c8190bb2d63c7fe0db2cc completed May 10, 2026, 1:42 p.m.
Created at: April 10, 2026, 5:18 a.m.