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From Drew Kutcharian <d...@venarc.com>
Subject Re: Can UIMA extract postal address information from text?
Date Thu, 24 Feb 2011 07:19:43 GMT
Hi Anuj,

Thank you for your quick reply. Do you know of any examples? Or can you help me do this (paid
work).
Like I said, I'm very new to NLP, so everything still looks a bit "magical".

- Drew


On Feb 23, 2011, at 11:16 PM, Anuj Kumar wrote:

> Hi Drew,
> 
> UIMA is an architecture and you can definitely plug in an algorithm to get
> your mailing address. This can be accomplished using some of the annotators
> provided out of the box by UIMA.
> 
> A simple way to accomplish this will be to have a dictionary of the
> countries, cities, street addresses, etc. and then use the dictionary,
> concept mapper or similar annotators that suit your need.
> 
> Hope it helps.
> 
> Regards,
> Anuj
> 
> On Thu, Feb 24, 2011 at 12:29 PM, Drew Kutcharian <drew@venarc.com> wrote:
> 
>> Hi Everyone,
>> 
>> I'm very new to text parsing/NLP and I was wondering if UIMA can be used to
>> extract mailing addresses from blocks of text, ie:
>> 
>> "Let's meet at 123 Evergreen St., Los Angeles, CA 90110 tomorrow at 10AM"
>> => "123 Evergreen St., Los Angeles, CA 90110"
>> 
>> If not, then what tools are out there that can help me accomplish this? Any
>> input is greatly appreciated.
>> 
>> 
>> Thanks,
>> 
>> Drew
>> 
>> 


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