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From "Dligach, Dmitriy" <Dmitriy.Dlig...@childrens.harvard.edu>
Subject Re: sentence detector model
Date Mon, 29 Sep 2014 15:32:47 GMT
Maybe creating a made-up set of sentences would be an option? That way we could agree on the
annotation of concrete cases. Although this would be more of a unit test than a corpus.

Dima




On Sep 27, 2014, at 12:15, Miller, Timothy <Timothy.Miller@childrens.harvard.edu> wrote:

> I've just been using the opennlp command line cross validator on the small dataset i
annotated (along with some eyeballing). It would be cool if there was a standard clinical
resource available for this task, but I hadn't considered it much because the data I annotated
pulls from multiple datasets and the process of  arranging with different institutions to
make something like that available would probably be a nightmare.
> Tim
> 
> Sent from my iPad. Sorry about the typos.
> 
>> On Sep 27, 2014, at 12:16 PM, "Dligach, Dmitriy" <Dmitriy.Dligach@childrens.harvard.edu>
wrote:
>> 
>> Tim, thanks for working on this!
>> 
>> Question: do we have some formal way of evaluating the sentence detector? Maybe we
should come up with some dev set that would include examples from mimic...
>> 
>> Dima
>> 
>> 
>> 
>> 
>>> On Sep 27, 2014, at 8:57, Miller, Timothy <Timothy.Miller@childrens.harvard.edu>
wrote:
>>> 
>>> I have been working on the sentence detector newline issue, training a model
to probabilistically split sentences on newlines rather than forcing sentence breaks. I have
checked in a model to the repo under ctakes-core-res. I also attached a patch to ctakes-core
to the jira issue:
>>> https://issues.apache.org/jira/browse/CTAKES-41
>>> 
>>> for people to test. The status of my testing is that it doesn't seem to break
on notes where ctakes worked well before (those where newlines are always sentence breaks),
and is a slight improvement on notes where newlines may or may not be sentence breaks. Once
the change is checked in we can continue improving the model by adding more data and features,
but the first hurdle I'd like to get past is making sure it runs well enough on the type of
data that the old model worked well on. Let me know if you have any questions.
>>> 
>>> Thanks
>>> Tim
>> 


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