Can UIMA extract postal address information from text?

[Drew Kutcharian <dr...@venarc.com>]

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

Re: Can UIMA extract postal address information from text?

[Drew Kutcharian <dr...@venarc.com>]

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 <dr...@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
>> 
>> 

Re: Can UIMA extract postal address information from text?

[Anuj Kumar <an...@gmail.com>]

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 <dr...@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
>
>