Hello Manoj,
This is more a job for Wikipedia than opennlp’s dev mail list.
https://en.wikipedia.org/wiki/Parsing <https://en.wikipedia.org/wiki/Parsing>
https://en.wikipedia.org/wiki/Shallow_parsing
<https://en.wikipedia.org/wiki/Shallow_parsing>
Essentially, the term “parsing” is a generic term that takes input text and
breaks it up into parts using certain rules (wikipedia refers to this as a
grammar). Think of java's Integer.parseInt(String s). OpenNLP has a
StringTokenizer that “parses” strings into constituent words based on
whitespace (WhitespaceTokenizer) or a statistically training model
(TokenizerME). A Chunker on the other hand takes the constituent words and
puts them together to make a larger construct (think of a phrase). So…. If
you want to get noun or verb phrases use a chunker. It is also very useful if
you are interested in identifying relationships between words. I believe the
Stanford NLP dependencies use chunking, for more info on that
https://nlp.stanford.edu/software/stanford-dependencies.shtml#English
<https://nlp.stanford.edu/software/stanford-dependencies.shtml#English> . If I
am wrong about the Stanford Dependencies, maybe someone will correct me...
Hope it helps,
Daniel
> On Aug 18, 2017, at 9:50 AM, Manoj B. Narayanan
> <[email protected]> wrote:
>
> Hi,
>
> Could someone help me with this please ?
>
> Thanks,
> Manoj.
>
> On Tue, Aug 8, 2017 at 1:16 PM, Manoj B. Narayanan <
> [email protected]> wrote:
>
>> Hi,
>>
>> Can some one please explain the difference between Parser and Chunker in
>> OpenNLP.
>> I think we can get the same output of the Parser from Chunker output
>> itself.
>> Please correct me if I am wrong.
>>
>> Thanks.
>> Manoj.
>>
