Hi, Sahar, I don't know a stabilished approach that solves your problem, but there are a few things you could try. For example, you could check if the sentence is parseable. If a Parser can figure out a tree for the sentence, it might mean that its structure is known. I don't know if it would work with a statistical parser like the one in OpenNLP, but it works at least for rule based parsers, were you have fine-grained control over the structures.
Regards, William On Tue, Apr 30, 2013 at 10:43 AM, Sahar Ebadi <[email protected]>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. >
