 import Foundation
 
 /**
-   Analyze various features of text content at scale. Provide text, raw HTML, or a public URL, and
-  IBM Watson Natural Language Understanding will give you results for the features you request. The
-  service cleans HTML content before analysis by default, so the results can ignore most
-  advertisements and other unwanted content.
-
-  ### Concepts
-  Identify general concepts that are referenced or alluded to in your content. Concepts that are
-  detected typically have an associated link to a DBpedia resource.
-
-  ### Entities
-  Detect important people, places, geopolitical entities and other types of entities in your
-  content. Entity detection recognizes consecutive coreferences of each entity. For example,
-  analysis of the following text would count "Barack Obama" and "He" as the same entity:
-
-  "Barack Obama was the 44th President of the United States. He took office in January 2009."
-
-  ### Keywords
-  Determine the most important keywords in your content. Keyword phrases are organized by relevance
-  in the results.
-
-  ### Categories
-  Categorize your content into a hierarchical 5-level taxonomy. For example, "Leonardo DiCaprio won
-  an Oscar" returns "/art and entertainment/movies and tv/movies" as the most confident
-  classification.
-
-  ### Sentiment
-  Determine whether your content conveys postive or negative sentiment. Sentiment information can be
-  returned for detected entities, keywords, or user-specified target phrases found in the text.
-
-  ### Emotion
-  Detect anger, disgust, fear, joy, or sadness that is conveyed by your content. Emotion information
-  can be returned for detected entities, keywords, or user-specified target phrases found in the
-  text.
-
-  ### Relations
-  Recognize when two entities are related, and identify the type of relation.  For example, you can
-  identify an "awardedTo" relation between an award and its recipient.
-
-  ### Semantic Roles
-  Parse sentences into subject-action-object form, and identify entities and keywords that are
-  subjects or objects of an action.
-
-  ### Metadata
-  Get author information, publication date, and the title of your text/HTML content.
+ Analyze various features of text content at scale. Provide text, raw HTML, or a public URL, and IBM Watson Natural
+ Language Understanding will give you results for the features you request. The service cleans HTML content before
+ analysis by default, so the results can ignore most advertisements and other unwanted content.
+ You can create <a target="_blank"
+ href="https://www.ibm.com/watson/developercloud/doc/natural-language-understanding/customizing.html">custom models</a>
+ with Watson Knowledge Studio that can be used to detect custom entities and relations in Natural Language
+ Understanding.
  */
 public class NaturalLanguageUnderstanding {
 

    /**
     List models.

     Lists available models for Relations and Entities features, including Watson Knowledge Studio custom models that you have created and linked to your Natural Language Understanding service.

     - parameter failure: A function executed if an error occurs.
     - parameter success: A function executed with the successful result.
    */
    public func listModels(
        failure: ((Error) -> Void)? = nil,
        success: @escaping (ListModelsResults) -> Void)

     - parameter username: The username used to authenticate with the service.
     - parameter password: The password used to authenticate with the service.
     - parameter version: The release date of the version of the API to use. Specify the date
     in "YYYY-MM-DD" format.
     */
    public init(username: String, password: String, version: String) {
        self.credentials = .basicAuthentication(username: username, password: password)
