Fix some typos in documentation.
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@ -509,7 +509,7 @@ it is just fine not to list the field to which the matches are combined
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Technically it is also fine to add fields to `matched_fields` that
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don't share the same underlying string as the field to which the matches
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are combined. The results might not make much sense and if one of the
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matches is off the end of the text then the whole the query will fail.
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matches is off the end of the text then the whole query will fail.
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[NOTE]
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===================================================================
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@ -53,5 +53,5 @@ query (just so there will be a place to set a name for it), for example:
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==== Named queries
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The support for the `_name` option on queries as available from version `0.90.4` and the support on filters is available
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The support for the `_name` option on queries is available from version `0.90.4` and the support on filters is available
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also in versions before `0.90.4`.
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@ -136,7 +136,7 @@ suggestion specific option. The suggest text specified on suggestion
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level override the suggest text on the global level.
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[float]
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=== Other suggest example.
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=== Other suggest example
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In the below example we request suggestions for the following suggest
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text: `devloping distibutd saerch engies` on the `title` field with a
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@ -11,8 +11,8 @@ suggest-selection is left to the API consumer. Yet, often pre-selected
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suggestions are required in order to present to the end-user. The
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`phrase` suggester adds additional logic on top of the `term` suggester
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to select entire corrected phrases instead of individual tokens weighted
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based on `ngram-langugage` models. In practice it this suggester will be
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able to make better decision about which tokens to pick based on
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based on `ngram-langugage` models. In practice this suggester will be
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able to make better decisions about which tokens to pick based on
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co-occurence and frequencies.
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==== API Example
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@ -33,7 +33,7 @@ doesn't take the query into account that is part of request.
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Defines how suggestions should be sorted per suggest text
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term. Two possible values:
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+
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** `score`: Sort by sore first, then document frequency and
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** `score`: Sort by score first, then document frequency and
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then the term itself.
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** `frequency`: Sort by document frequency first, then similarity
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score and then the term itself.
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