Hi Sahar,
Only problem with a rule based parser is that there are always
exceptions to the rule.
Regards,
James
On 5/6/2013 8:36 AM, William Colen wrote:
Hi, Sahar,
I don't know any open source rule based parser, but probably there is.
I only know a proprietary one called EngGram, which is built with
Constraint Grammar (GPL).
You can use EngGram online here:
http://beta.visl.sdu.dk/visl/en/parsing/automatic/
Regards,
William
On Fri, May 3, 2013 at 12:06 PM, Sahar Ebadi <[email protected]>wrote:
Hi,
Thanks for the replies! :)
Lance:
1)yes, I use sentence detector just to split the text in to sentences and I
am not taking them as like they are Valid sentences.
2)Watson goes beyond what I need. I only need to find good/valid sentences
in the text(only NLP, does not include reasoning and information retrival
as watson does).
3)I know there should be some semi-effective solutions but I am not able to
find them. can you give me some keywords or short explanation on some of
them? that would be a greaat help!!
So what I have done:
the only solution I found was to parse the sentence and then check to see
if it follows the standard grammatical pattern of a sentence. If so it is a
valid sentence otherwise it is not a valid sentence. so far, I have parsed
the sentences using Open NLP which is tagged based on penn treebank. now I
need to know if there is any standard sentence pattern which is based on
penn treebank?
Ryan: the result will not be accurate enough.
Willian: can you pass me the name of some rule-based parser you have in
mind? (especially those compatible with OPEN NLP)
I really appreciate any suggestions on this.
Thank you all so much!
On Wed, May 1, 2013 at 5:34 PM, Lance Norskog <[email protected]> wrote:
The "sentence detector" is for tokenizing (breaking text into words), not
analysis.
The 'brute force' approach for removing non-english texts is to search
for
higher-page Unicode. If it's over 255, it's not english. (Except maybe
for
currency.)
What you're talking about are semantically deep problems that have a lot
of semi-effective solutions. How deep do you want this analysis to be?
How
close to IBM Watson do you expect to get?
On 04/30/2013 06:43 AM, Sahar Ebadi wrote:
Hi all,
lets say I have a text and I would like to detect only "good sentences".
by
"good sentences" I mean sentences that are 1)complete( grammatically
2)have meaning 3)are in English language.
As far as I found Open NLP sentence detector only detects sentences
according to punctuation(and a list of acronyms it has), so there is
no guarantee that the sentences are real, complete and meaningful
sentences.
Now my question is is there any process in NLP that can help me to :
1)find grammatically complete sentences?
2)find if a sentence has meaning or no?
3)filter non-english texts?
any suggestions or sharing useful resources is highly appreciated!
Thanks.
