opennlp-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Jörn Kottmann <>
Subject Re: How to work with Coreference resolutions
Date Thu, 14 Jun 2012 15:14:42 GMT

the input for the coreference component needs to be preprocessed,
with the sentence detector, tokenizer, parser and name finders.

You can do this via API and our documentation provides sample code for
each of these steps.

The only tricky part is the to get the named entities into the parse tree.
Here is a sample:
Parse parse; // returned from parser
Span personEntites[];  // returned from person name model
Parse.addNames("person", personEntites[fi], parse.getTagNodes());

After this the person names are inserted into the parse tree, you need
to repeat this step for every entity type you would like to reference. 
The "person"
tags are currently hard coded. You can find a list in 
(I believe thats a trunk only class).

Before you start with the rest you should download all the coreferencer 
models for 1.4
into one directory, similar to the structure on the sever.

Now we are coming to the coreference resolution code:
Linker treebankLinker = new TreebankLinker("/home/joern/corefmodel/", 

This will create the linker for you.

First all the mentions need to be recognized and afterward they are 
linked together.
For every sentence you do this:
Parse p = ...; // contains a parse of a sentence with names
Mention[] extents = treebankLinker.getMentionFinder().getMentions(new 
for (int ei=0,en=extents.length;ei<en;ei++) {
   if (extents[ei].getParse() == null) {
     Parse snp = new Parse(p.getText(),extents[ei].getSpan(),"NML",1.0,0);
     extents[ei].setParse(new DefaultParse(snp, sentenceNumber));

The result are the mentions per sentence. All these mention objects 
should be copied into a single list,
e.g. via document.addAll(extents) (document is of type List<Mention>).

Now the mentions of one document can be linked together:
DiscourseEntity[] entities = 
treebankLinker.getEntities(document.toArray(new Mention[document.size()]));

The entities array now contains the various detected and linked 
entities, usually you want to filter out entities
which just have a single mention. The DiscourseEntity groups mentions 
together, a mention must not be an
entity, other noun phrases are valid mentions as well.

Hope that helps,

On 06/13/2012 07:41 PM, Carlos Scheidecker wrote:
> Jörn,
> I just want to know how it works for now. I've following the one from
> StanfordNLP as well.
> Basically, I want to first know if I just pass raw test to it or if I have
> to tag that first. Looks like I need to do POS tag first.
> I want to be able to pass a text and get the references as object lists
> from the API.
> So I can fetch the relations.
> I still need to take some time here and read more the source code unless
> you have some pointers.
> Thanks,
> Carlos.
> On Wed, Jun 13, 2012 at 11:23 AM, Jörn Kottmann<>  wrote:
>> On 06/13/2012 07:07 PM, Carlos Scheidecker wrote:
>>> Thanks. So for now we can only use the models from 1.4. I saw that a
>>> training class was added recently. How do you use that?
>> Thats still work in progress, on which data do you want to train?
>> You need to produce data in a certain format, there should be a sample in
>> the test folder.
>> Its basically penn treebank style plus some nodes to label the mentions
>> in the tree.
>> The parse trees of a document are grouped and send document wise
>> to the trainer via a stream. After this is done a new model will be
>> trained.
>> The OpenNLP corferencer works currently only on noun phrases, other
>> mentions
>> like verbs will not be resolved (in case you wanna train on OntoNotes).
>> Jörn

View raw message