[Corpora-List] Off-the-shelf coreference packages

[Bill_Lang(Gmail)]

Reconcile is great. Thanks for the authors sharing. It should be a nice
platform for researchers who are fresh to coreference resolution.

Best Wishes;
Lang Jun

2011/7/19 Jason Eisner <jason at cs.jhu.edu>

> Reconcile was released last year as an common platform for coref, with
> up-to-date methods and good performance out of the box.
> http://www.cs.utah.edu/nlp/reconcile/
>
> "Reconcile is an automatic coreference resolution system that was developed
> to provide a stable test-bed for researchers to implement new ideas quickly
> and reliably. It achieves roughly state of the art performance on many of
> the most common coreference resolution test sets, such as MUC-6, MUC-7, and
> ACE. Reconcile comes ready out of the box to train and test on these common
> data sets (though the data sets are not provided) as well as the ability to
> run on unlabeled texts. Reconcile utilizes supervised machine learning
> classifiers from the Weka toolkit, as well as other language processing
> tools such as the Berkeley Parser and Stanford Named Entity Recognition
> system.   The source language is Java, and it is freely available under the
> GPL."
>
> On Mon, Jul 18, 2011 at 1:24 PM, Leon Derczynski <leon at dcs.shef.ac.uk>wrote:
>
>> Hi,
>>
>> What off-the-shelf coreference resolution packages would you recommend? So
>> far I have Arkref, Stanford coref and BART working, and all seem to produce
>> unsatisfactory results too often to be useful in practice. Is this
>> characteristic of the state of the art?
>>
>> The text that I am trying to process is plaintext English newswire, and
>> the entity types that I am most interested in resolving correctly are people
>> and organisations. However currently at least one major actor per document
>> appears to be incorrectly conflated with another entity; the president of
>> the USA with an aircraft carrier, or "sanctions" with a country. Any tips or
>> links to downlaodable systems would be greatly appreciated.
>>
>> All the best,
>>
>>
>> Leon
>>
>>
>>
>> --
>> Leon R A Derczynski
>> NLP Research Group
>>
>> Department of Computer Science
>> University of Sheffield
>> Regent Court, 211 Portobello
>> Sheffield S1 4DP, UK
>>
>> +44 114 22 21931
>> http://www.dcs.shef.ac.uk/~**leon/ <http://www.dcs.shef.ac.uk/%7Eleon/>
>>
>>
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>
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