Triple

T8742346
Position Surface form Disambiguated ID Type / Status
Subject Moscow Art Theatre E207533 entity
Predicate shortName P43 FINISHED
Object MAT
MAT is the commonly used abbreviation for the Moscow Art Theatre, a historic and influential Russian theatre company renowned for its pioneering work in modern drama and acting techniques.
 E754474 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: MAT | Statement: [Moscow Art Theatre, shortName, MAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAT
Context triple: [Moscow Art Theatre, shortName, MAT]
  • A. Mat
    Mat is a common shortened form of the given name Matthew, often used as an informal or familiar nickname.
  • B. MT
    MT is the stock ticker symbol for ArcelorMittal, one of the world’s largest steel and mining companies.
  • C. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • D. MATE
    MATE is a lightweight, traditional-style desktop environment for Unix-like operating systems, derived from GNOME 2 and focused on simplicity and low resource usage.
  • E. MTAB
    MTAB is the operator code used to identify the MTA New York City Bus division within the Metropolitan Transportation Authority’s transit operations.
  • 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: MAT
Triple: [Moscow Art Theatre, shortName, MAT]
Generated description
MAT is the commonly used abbreviation for the Moscow Art Theatre, a historic and influential Russian theatre company renowned for its pioneering work in modern drama and acting techniques.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAT
Target entity description: MAT is the commonly used abbreviation for the Moscow Art Theatre, a historic and influential Russian theatre company renowned for its pioneering work in modern drama and acting techniques.
  • A. Mat
    Mat is a common shortened form of the given name Matthew, often used as an informal or familiar nickname.
  • B. MT
    MT is the stock ticker symbol for ArcelorMittal, one of the world’s largest steel and mining companies.
  • C. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • D. MATE
    MATE is a lightweight, traditional-style desktop environment for Unix-like operating systems, derived from GNOME 2 and focused on simplicity and low resource usage.
  • E. MTAB
    MTAB is the operator code used to identify the MTA New York City Bus division within the Metropolitan Transportation Authority’s transit operations.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d6fd5dc8190906b7147f27c5d46 completed March 31, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42f282e48190ad158063e265e0f0 completed April 3, 2026, 4:32 a.m.
NEDg Description generation batch_69cf4433605c8190991f95d19726cab8 completed April 3, 2026, 4:38 a.m.
NED2 Entity disambiguation (via description) batch_69cf44c20b408190b622d18f78277802 completed April 3, 2026, 4:40 a.m.
Created at: March 30, 2026, 6:38 p.m.