Features Structure Reference


                    
                    
                    classifications

Returns text classifications for the content. Supported languages: English only.

Declaration

Swift

public var classifications: ClassificationsOptions?


                    
                    
                    concepts

Returns high-level concepts in the content. For example, a research paper about deep learning might return the concept, “Artificial Intelligence” although the term is not mentioned. Supported languages: English, French, German, Italian, Japanese, Korean, Portuguese, Spanish.

Declaration

Swift

public var concepts: ConceptsOptions?


                    
                    
                    emotion

Detects anger, disgust, fear, joy, or sadness that is conveyed in the content or by the context around target phrases specified in the targets parameter. You can analyze emotion for detected entities with entities.emotion and for keywords with keywords.emotion. Supported languages: English.

Declaration

Swift

public var emotion: EmotionOptions?


                    
                    
                    entities

Identifies people, cities, organizations, and other entities in the content. For more information, see Entity types and subtypes. Supported languages: English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish, Swedish. Arabic, Chinese, and Dutch are supported only through custom models.

Declaration

Swift

public var entities: EntitiesOptions?


                    
                    
                    keywords

Returns important keywords in the content. Supported languages: English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish, Swedish.

Declaration

Swift

public var keywords: KeywordsOptions?


                    
                    
                    metadata

Returns information from the document, including author name, title, RSS/ATOM feeds, prominent page image, and publication date. Supports URL and HTML input types only.

Declaration

Swift

public var metadata: [String : JSON]?


                    
                    
                    relations

Recognizes when two entities are related and identifies the type of relation. For example, an awardedTo relation might connect the entities “Nobel Prize” and “Albert Einstein”. For more information, see Relation types. Supported languages: Arabic, English, German, Japanese, Korean, Spanish. Chinese, Dutch, French, Italian, and Portuguese custom models are also supported.

Declaration

Swift

public var relations: RelationsOptions?


                    
                    
                    semanticRoles

Parses sentences into subject, action, and object form. Supported languages: English, German, Japanese, Korean, Spanish.

Declaration

Swift

public var semanticRoles: SemanticRolesOptions?


                    
                    
                    sentiment

Analyzes the general sentiment of your content or the sentiment toward specific target phrases. You can analyze sentiment for detected entities with entities.sentiment and for keywords with keywords.sentiment. Supported languages: Arabic, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish.

Declaration

Swift

public var sentiment: SentimentOptions?


                    
                    
                    summarization

(Experimental) Returns a summary of content. Supported languages: English only.

Declaration

Swift

public var summarization: SummarizationOptions?


                    
                    
                    categories

Returns a five-level taxonomy of the content. The top three categories are returned. Supported languages: Arabic, English, French, German, Italian, Japanese, Korean, Portuguese, Spanish.

Declaration

Swift

public var categories: CategoriesOptions?


                    
                    
                    syntax

Returns tokens and sentences from the input text.

Declaration

Swift

public var syntax: SyntaxOptions?


                    
                    
                    init(classifications:concepts:emotion:entities:keywords:metadata:relations:semanticRoles:sentiment:summarization:categories:syntax:)

Initialize a Features with member variables.

Declaration

Swift

public init(
    classifications: ClassificationsOptions? = nil,
    concepts: ConceptsOptions? = nil,
    emotion: EmotionOptions? = nil,
    entities: EntitiesOptions? = nil,
    keywords: KeywordsOptions? = nil,
    metadata: [String: JSON]? = nil,
    relations: RelationsOptions? = nil,
    semanticRoles: SemanticRolesOptions? = nil,
    sentiment: SentimentOptions? = nil,
    summarization: SummarizationOptions? = nil,
    categories: CategoriesOptions? = nil,
    syntax: SyntaxOptions? = nil
)

Parameters

`classifications`	Returns text classifications for the content. Supported languages: English only.
`concepts`	Returns high-level concepts in the content. For example, a research paper about deep learning might return the concept, “Artificial Intelligence” although the term is not mentioned. Supported languages: English, French, German, Italian, Japanese, Korean, Portuguese, Spanish.
`emotion`	Detects anger, disgust, fear, joy, or sadness that is conveyed in the content or by the context around target phrases specified in the targets parameter. You can analyze emotion for detected entities with `entities.emotion` and for keywords with `keywords.emotion`. Supported languages: English.
`entities`	Identifies people, cities, organizations, and other entities in the content. For more information, see Entity types and subtypes. Supported languages: English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish, Swedish. Arabic, Chinese, and Dutch are supported only through custom models.
`keywords`	Returns important keywords in the content. Supported languages: English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish, Swedish.
`metadata`	Returns information from the document, including author name, title, RSS/ATOM feeds, prominent page image, and publication date. Supports URL and HTML input types only.
`relations`	Recognizes when two entities are related and identifies the type of relation. For example, an `awardedTo` relation might connect the entities “Nobel Prize” and “Albert Einstein”. For more information, see Relation types. Supported languages: Arabic, English, German, Japanese, Korean, Spanish. Chinese, Dutch, French, Italian, and Portuguese custom models are also supported.
`semanticRoles`	Parses sentences into subject, action, and object form. Supported languages: English, German, Japanese, Korean, Spanish.
`sentiment`	Analyzes the general sentiment of your content or the sentiment toward specific target phrases. You can analyze sentiment for detected entities with `entities.sentiment` and for keywords with `keywords.sentiment`. Supported languages: Arabic, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish.
`summarization`	(Experimental) Returns a summary of content. Supported languages: English only.
`categories`	Returns a five-level taxonomy of the content. The top three categories are returned. Supported languages: Arabic, English, French, German, Italian, Japanese, Korean, Portuguese, Spanish.
`syntax`	Returns tokens and sentences from the input text.

Return Value

An initialized Features.