I know, it's hideous.

They typically consist of an "entity" neared with a large number of 
"negative" (user specified) terms.  So something like [bad person near50 
(long or list near5 negative or terms ...)] which we translate into a big 
horrible near_span query.  When we can detect a language then we can apply 
one analyzer and query the appropriate fields.  Otherwise, we query across 
a number of fields with different language analyzed fields.  It's not nice.

It's pretty typical in certain industries.

On Thursday, 10 April 2014 00:03:48 UTC+1, hazzadous wrote:
>
> No you don't Binh
>
> On Wednesday, 9 April 2014 17:57:17 UTC+1, Binh Ly wrote:
>>
>> I'd be curious to see an example of such a query! :)
>>
>

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