I'm trying to use the CLI. I have other code in another project that
loads the dictionary properly using the property file to specify the
information. Coreference does it differently...
On 3/2/2013 6:32 AM, Jim - FooBar(); wrote:
I should be able to help you...are you going through the cli or the
API? I bet there is something wrong with the Wordnet directory you're
passing...I had similar issues...
If you're using the API let me know and I'll send you a code snippet
that may help...
Jim
On 02/03/13 05:17, James Kosin wrote:
Jim,
I can't seem to get past the NULL pointer exceptions when
Coreferencer is trying to load the dictionaries. So, this will be
much later now. I'm going to sleep and play tooth fairy.
James
On 3/1/2013 8:18 AM, Jim - FooBar(); wrote:
Like you, I'm using the latest WOrdnet and JWNL (1.4 RC_3 is on
maven you don't need to build it from source)....
Now that you've set up your end could you please perform a run on
the standard example sentence? In addition could you try to add the
named-entities to the parse-tree?
If yes, please post your results here for comparison with mine?
thanks a lot,
Jim
On 01/03/13 02:21, James Kosin wrote:
Hi Jim,
What version of the JWNL and WordNet dictionaries are you using?
I never got much more than researching what it is used for, and its
importance to handling the task.
I've just updated my end for the 3.1 WordNet dictionaries. But, I'm
also using 1.4_rc3 from sources to build JWNL. The extJWNL seems
to be more apt to handling more types of dictionaries (supporting
UTF-8 and others), and actually creating and modifying them as
well; which isn't needed when we are really only wanting read usage.
James
On 2/28/2013 4:49 AM, Jim foo.bar wrote:
Hi James,
thanks for your reply and your comments but that is not quite what
I asked...I've looked at all the web resources related to the
opennlp coref component, otherwise I would never have gotten it to
work!
My problem is about the results it brings back, in particular I'd
like to compare my produced discourse entities with someone
else's on the same piece of text. Since I'm working on a language
other than Java, that would confirm that my code is at least
correct. On a secondary note, I'd like to see how to insert the
named-entities into the parse tree before deploying the
TrreBankLinker. I followed the instructions posted my Jorn
sometime last year but I 'm not sure how the output should look
like .That is why I posted what I'm getting...Can you see any
'person' named-entities in my DicourseEntities?
More importantly, if you run the coref component on the standard
example sentence (Pierre Vinken, ...) what do you get? Could you
post the exact output?
Whoever psoted this:
http://blog.dpdearing.com/2012/11/making-coreference-resolution-with-opennlp-1-5-0-your-bitch/
did not try to insert any NEs into the parse tree. In addition,
his output is slightly different than mine...I don't know if that
is because of a newer version of JWNL.jar that I'm using or
something else...
Jim
On 28/02/13 02:51, James Kosin wrote:
Jim,
Here is a place to start, with maybe some more examples:
http://stackoverflow.com/questions/8629737/coreference-resolution-using-opennlp
James
On 2/27/2013 1:26 PM, Jim - FooBar(); wrote:
Hmmm.... interesting! When I run it on these 2 simple sentences:
/"Mary likes pizza but she also likes kebabs. Knowing her, I'd
give it 2 weeks before she turns massive!"/
I get perfect results!
#<DiscourseEntity [ Mary, she, her, she ]>
this demonstrates 3 things:
- my understanding of coref is indeed correct
- the coref component can link entities from separate sentences
- possibly that my code is fine
any thoughts?
Jim
On 27/02/13 18:14, Jim - FooBar(); wrote:
Hi all,
I finally managed to get coref working (phew!-my god that was
tricky) but I'm slightly confused with the results so I'd like
to see if anyone else has tried that out...Using the standard
paragraph used in the other examples:
/"Pierre Vinken, 61 years old, will join the board as a
nonexecutive director Nov. 29. Mr. Vinken is chairman of
Elsevier N.V., the Dutch publishing group. Rudolph Agnew, 55
years old and former chairman of Consolidated Gold Fields PLC,
was named a director of this British industrial conglomerate."/
deploying the coref component gives me the following:
I must note that I'm trying to pass the named entities as well
(person). I've confirmed that the spans are correctly
identitified (3 spans for this particular example) and added to
the parse tree via
/opennlp.tools.parser.Parse.addNames//("person", span,
parse.getTagNodes());/
[#<DiscourseEntity [ this British industrial conglomerate ]>,
#<DiscourseEntity [ a director of this British industrial
conglomerate ]>,
#<DiscourseEntity [ Consolidated Gold Fields PLC ]>,
#<DiscourseEntity [ chairman of Elsevier N . V . , the Dutch
publishing group, former chairman of Consolidated Gold Fields
PLC ]>,
#<DiscourseEntity [ 55 years ]>,
#<DiscourseEntity [ Rudolph Agnew , 55 years old and former
chairman of Consolidated Gold Fields PLC , was named a director
of this British industrial conglomerate . ]>,
#<DiscourseEntity [ Elsevier N . V . , the Dutch publishing
group, the Dutch publishing group ]>,
#<DiscourseEntity [ Mr . Vinken ]>,
#<DiscourseEntity [ a nonexecutive director Nov . 29 ]>,
#<DiscourseEntity [ the board ]>,
#<DiscourseEntity [ 61 years ]>,
#<DiscourseEntity [ Pierre Vinken , 61 years old ]>
]
*filtering for more than 1 mentions (per Jorn's suggestion)
gives back:*
[#<DiscourseEntity [ chairman of Elsevier N . V . , the Dutch
publishing group, former chairman of Consolidated Gold Fields
PLC ]>
#<DiscourseEntity [ Elsevier N . V . , the Dutch publishing
group, the Dutch publishing group ]>
]
Assuming that this is what it's supposed to output, can someone
explain this? First of all where are the named-entities?
Secondly, out of the 2 filtered DiscourseEntities, both seem
plain wrong! Moreover, where is #<DiscourseEntity [Rudolph
Agnew, //former chairman of Consolidated Gold Fields PLC/,/ the
Dutch publishing group, director of this British industrial
conglomerate ]> ???
Either I'm not understanding coreference, or I've coded the
thing wrong or the models is not very good! Which one is it?
Has anyone else attempted this? Can we compare results on this
particular sentence?
thanks in advance :)
Jim
ps: my code is in Clojure but it is based on a code snippet
provided by Jorn to someone on the mailing list last year . I
can easily provide it but I don't think it will be of much help...
