Hello,

Ratnapharki's (1999) is a shift-reduced parser. Others like Stanford
NLP are now releasing shift-reduced parsers. There are differences
between them, though. For example, Zhang and Clark (2009)'s parser
(cited by Stanford's new parser) is similar except that they use a
global discriminative model applying Collins (2002) perceptron,
whereas
Ratnaparkhi’s parser has separate probabilities of actions chained
together in a conditional model (based on ME).

Perhaps that route, among others, would be an interesting one to have
a new parser in opennlp.

Cheers,

Rodrigo



On Sun, Jun 22, 2014 at 9:44 PM, Richard Eckart de Castilho
<[email protected]> wrote:
> Some time ago I asked the mstparser developers if they would consider
> contributing the parser to OpenNLP. They said that mstparser isn't
> up-to-date anymore since better parsers are now available, but in
> principle didn't reject the idea.
>
> If OpenNLP was interested in adopting the mstparser, that might
> be something to follow up on.
>
> The mstparser is only a dependency parser, not a constituency parser
> as the one currently included with OpenNLP.
>
> Cheers,
>
> -- Richard
>
> On 20.06.2014, at 09:33, Jörn Kottmann <[email protected]> wrote:
>
>> On 06/19/2014 06:00 PM, Miller, Timothy wrote:
>>> There is a paper at this year's ACL conference on a statistical parser
>>> with some interesting properties [1]. I tracked down the software [2]
>>> and it is apache-licensed (unlike most other high quality parsers such
>>> as the Berkeley and Stanford parsers). It is written in Scala so in
>>> theory it should be compatible. Most importantly it is about as accurate
>>> as those state of the art parsers on English (about 33% error reduction
>>> from the Ratnaparkhi parser that opennlp currently uses), and may be
>>> superior for cross-language performance.
>>>
>>> I am going to play with it with some of our clinical data to get a feel
>>> for speed/accuracy on clinical text. Just curious if there is any
>>> interest in a wrapper for this parser in opennlp?
>>
>> I don't think a wrapper is interesting for us. If people want to use this 
>> parser it is probably
>> better if they integrate it directly or use a component framework like UIMA 
>> or GATE.
>>
>> Anyway, getting a new parser as a contribution would be interesting.
>>
>> Jörn
>

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