+1, it would be possible to include different styles and
implementations of parsers in OpenNLP.
Jörn
On 06/23/2014 01:12 PM, Rodrigo Agerri wrote:
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
