Triple

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).

Phrase: BR-MS | Statement: [Mato Grosso do Sul, ISO3166-2, BR-MS]

Target entity: BR-MS
Context triple: [Mato Grosso do Sul, ISO3166-2, BR-MS]

• A. BR2
  BR2 is a UK postcode district covering parts of Hayes and surrounding areas in the London Borough of Bromley in southeast England.
• B. BRIN
  BRIN (Block Range Index) is a lightweight PostgreSQL index type optimized for very large tables by summarizing ranges of physical data blocks instead of indexing every individual row.
• C. MSA
  MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
• D. MSA
  MSA is a common abbreviation for a metropolitan statistical area, a region defined by the U.S. Office of Management and Budget for statistical and demographic analysis.
• E. MSA
  MSA is the commonly used abbreviation for the Magnuson–Stevens Fishery Conservation and Management Act, the primary law governing marine fisheries management in U.S. federal waters.
• F. None of above. chosen
• G. Unsure - the case is ambiguous/there is not enough information to decide.

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]"

Entity: BR-MS
Triple: [Mato Grosso do Sul, ISO3166-2, BR-MS]

BR-MS is the ISO 3166-2 subdivision code that uniquely identifies the Brazilian state of Mato Grosso do Sul.

Target entity: BR-MS
Target entity description: BR-MS is the ISO 3166-2 subdivision code that uniquely identifies the Brazilian state of Mato Grosso do Sul.

• A. BR2
  BR2 is a UK postcode district covering parts of Hayes and surrounding areas in the London Borough of Bromley in southeast England.
• B. BRIN
  BRIN (Block Range Index) is a lightweight PostgreSQL index type optimized for very large tables by summarizing ranges of physical data blocks instead of indexing every individual row.
• C. MSA
  MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
• D. MSA
  MSA is a common abbreviation for a metropolitan statistical area, a region defined by the U.S. Office of Management and Budget for statistical and demographic analysis.
• E. MSA
  MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
• F. None of above. chosen