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[java-nlp-user] 答复: NER - CRFClassifier Classes

Gerber Daniel dgerber at
Thu Apr 7 06:29:41 PDT 2011

Thanks for your answer.

I've tried to train the classifier with my annotated file (as described at This seems to work well with the Stanford NER package. However I'm using the (most-recent) Stanford-CoreNLP in my project and with this, it's not possible to train the classifier nor to load the trained one (from NER package). I'm getting this error message:

Exception in thread "main" java.lang.RuntimeException: edu.stanford.nlp.util.Index; local class incompatible: stream classdesc serialVersionUID = 5398562825928375260, local class serialVersionUID = 533612384823468898

I know multiple people dealt with this error before, but I found no real answer to my problem. Is there any way to train my model with this release?

One more thing: Is it somehow possible to add the trained DATE class to let's say the "conll.closed.iob2.crf"-classifier? I would really like to avoid recreating it or using different classifiers in my code?

Kind regards,

P.S.: I would be happy to share my results with this list.

On 28.03.2011, at 20:29, Dakan Wang wrote:

> Hi,
> 1. For a detailed description of the data, check
> The MISC means any type other than PERSON, ORGANIZATION, LOCATION.
> 2. If you have a new entity type, you should train your own classifier and
> provide enough entities for the new type so that the classifier can learn
> from your data. For how to train your own classifier, check
> Dakan.
> -----邮件原件-----
> 发件人: java-nlp-user-bounces at
> [mailto:java-nlp-user-bounces at] 代表 Gerber Daniel
> 发送时间: 2011年3月28日 2:43
> 收件人: java-nlp-user at
> 主题: [java-nlp-user] NER - CRFClassifier Classes
> Hi all,
> I've integrated the AbstractSequenceClassifier into my software research
> project. Therefore I loaded the "conll.closed.iob2.crf.ser.gz"
> CRFClassifier. The classes supported by this classifier seem to be PERSON,
> ORGANIZATION, LOCATION and MISC. So my first question is: 
> 1. What exactly does MISC stand for?
> And the second question is:
> 2. Is there any way (preferably, without to train my own classifier) to also
> support the class DATE?
> Kind regards,
> Daniel
> _______________________________________________
> java-nlp-user mailing list
> java-nlp-user at

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