anchor.diff:      suggestion should appear in. This can be specified as an absolute number
       or as a relative percentage of number of documents. This can improve
       quality by only suggesting high frequency terms. Defaults to 0f and is
  -    not enabled. If a value higher than 1 is specified then the number
  +    not enabled. If a value higher than 1 is specified, then the number
       cannot be fractional. The shard level document frequencies are used for
       this option.
   
   `max_term_freq`::
  -    The maximum threshold in number of documents a
  +    The maximum threshold in number of documents in which a
       suggest text token can exist in order to be included. Can be a relative
  -    percentage number (e.g 0.4) or an absolute number to represent document
  -    frequencies. If an value higher than 1 is specified then fractional can
  +    percentage number (e.g., 0.4) or an absolute number to represent document
  +    frequencies. If a value higher than 1 is specified, then fractional can
       not be specified. Defaults to 0.01f. This can be used to exclude high
  -    frequency terms from being spellchecked. High frequency terms are
  -    usually spelled correctly on top of this also improves the spellcheck
  -    performance. The shard level document frequencies are used for this
  -    option.
  +    frequency terms -- which are usually spelled correctly -- from being spellchecked.
  +    This also improves the spellcheck performance. The shard level document frequencies
  +    are used for this option.
   
   `string_distance`::
       Which string distance implementation to use for comparing how similar
       suggested terms are. Five possible values can be specified:
  -    `internal` - The default based on damerau_levenshtein but highly optimized
  +    
  +    ** `internal`: The default based on damerau_levenshtein but highly optimized
       for comparing string distance for terms inside the index.
  -    `damerau_levenshtein` - String distance algorithm based on
  +    ** `damerau_levenshtein`: String distance algorithm based on
       Damerau-Levenshtein algorithm.
  -    `levenshtein` - String distance algorithm based on Levenshtein edit distance
  +    ** `levenshtein`: String distance algorithm based on Levenshtein edit distance
       algorithm.
  -    `jaro_winkler` - String distance algorithm based on Jaro-Winkler algorithm.
  -    `ngram` - String distance algorithm based on character n-grams.
  +    ** `jaro_winkler`: String distance algorithm based on Jaro-Winkler algorithm.
  +    ** `ngram`: String distance algorithm based on character n-grams.
  
positive.code: 
  `field`::
      The field to fetch the candidate suggestions from. This is
      an required option that either needs to be set globally or per
      suggestion.
  
  `analyzer`::
  
negative.code: 
  [horizontal]
  `lowercase_terms`::
      Lowercases the suggest text terms after text analysis.
  
  `max_edits`::
      The maximum edit distance candidate suggestions can
      have in order to be considered as a suggestion. Can only be a value
      between 1 and 2. Any other value results in a bad request error being
      thrown. Defaults to 2.
  
  `prefix_length`::
      The number of minimal prefix characters that must
      match in order be a candidate for suggestions. Defaults to 1. Increasing
      this number improves spellcheck performance. Usually misspellings don't
      occur in the beginning of terms. (Old name "prefix_len" is deprecated)
  
  