In the context of supervised learning approach,I would like to know which is the most appropriate method to extract pertinent information from annotated text, notably the identification of relation between named entities whithin a sentence.
I agree with Ugur, the information extraction process is largely dependent on your data distribution. Since you want to find the relation between named entities, try support vector machines. Moreover, you can try pattern recognition and various text mining techniques and compare the performance.
Dear friend
You can use kernel based learning....thats better....
Dear Ines,
Though information extraction is highly data dependent, still Kernel based information extraction is more advanced approach for such cases. It certainly gives a better result compared to feature based information extraction.
Don't forget to consider possibilities for pre-processing the data. These could influence which technique is better.
Thanks a lot for your pertinent responses. I will take into account all your remarks.
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