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: Beijing Nanyuan Airport | Statement: [China United Airlines, formerHub, Beijing Nanyuan Airport]

Target entity: Beijing Nanyuan Airport
Context triple: [China United Airlines, formerHub, Beijing Nanyuan Airport]

• A. Beijing Capital International Airport
  Beijing Capital International Airport is the main international gateway to China’s capital and one of the busiest airports in the world by passenger traffic.
• B. Tianjin Binhai International Airport
  Tianjin Binhai International Airport is a major air transport hub serving the city of Tianjin and the wider Beijing–Tianjin–Hebei region in northern China.
• C. Beihai Fucheng Airport
  Beihai Fucheng Airport is a regional civil airport serving the coastal city of Beihai in Guangxi, China, providing domestic flights and connections to major Chinese cities.
• D. Wuhan Tianhe International Airport
  Wuhan Tianhe International Airport is a major aviation hub in central China serving the city of Wuhan with extensive domestic and international flight connections.
• E. Shenyang Taoxian International Airport
  Shenyang Taoxian International Airport is the main international airport serving Shenyang and the surrounding region in northeastern China.
• 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: Beijing Nanyuan Airport
Triple: [China United Airlines, formerHub, Beijing Nanyuan Airport]

Beijing Nanyuan Airport was a historic, now-closed airport in southern Beijing that primarily handled domestic flights and served as a military-civilian facility.

Target entity: Beijing Nanyuan Airport
Target entity description: Beijing Nanyuan Airport was a historic, now-closed airport in southern Beijing that primarily handled domestic flights and served as a military-civilian facility.

• A. Beijing Capital International Airport
  Beijing Capital International Airport is the main international gateway to China’s capital and one of the busiest airports in the world by passenger traffic.
• B. Tianjin Binhai International Airport
  Tianjin Binhai International Airport is a major air transport hub serving the city of Tianjin and the wider Beijing–Tianjin–Hebei region in northern China.
• C. Beihai Fucheng Airport
  Beihai Fucheng Airport is a regional civil airport serving the coastal city of Beihai in Guangxi, China, providing domestic flights and connections to major Chinese cities.
• D. Wuhan Tianhe International Airport
  Wuhan Tianhe International Airport is a major aviation hub in central China serving the city of Wuhan with extensive domestic and international flight connections.
• E. Shenyang Taoxian International Airport
  Shenyang Taoxian International Airport is the main international airport serving Shenyang and the surrounding region in northeastern China.
• F. None of above. chosen

Target predicate: formerHub
Context triple: [China United Airlines, formerHub, Beijing Nanyuan Airport]

• A. hubFor chosen
  Indicates that one entity serves as a central node or focal point through which activities, connections, or resources related to another entity are organized or routed.
• B. formerUrl
  Indicates that one entity was previously identified or accessible via the URL represented by the other entity, but that URL is no longer current.
• C. formerFocus
  Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
• D. formerProduct
  Indicates that an entity was previously a product of another entity but is no longer in that role or status.
• E. formerSiteOf
  Indicates that a location previously hosted or contained something (such as a structure, organization, or event) that is no longer present there.
• F. None of above.