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jiesutd / LatticeLSTM

Chinese NER using Lattice LSTM. Code for ACL 2018 paper.
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About the annotation of the Resume dataset #39

Closed Kiwisher closed 5 years ago

Kiwisher commented 5 years ago

Hi. I'm now dealing with some clinical unannotated data and I wonder how did you manually annotate the resume data in your experiment. Did you use some tricks or ML based annotatation? Thanks XD.

jiesutd commented 5 years ago

Our resume data is annotated with our annotation YEDDA. It is very efficient and simple to annotation the tasks as named entity recognition. As the resume data is relatively small, we annotate them manually without any ML techs.

If your data is large, then you can use a pretrained model to pre-annotate your data and manually finetune them. Our annotation YEDDA system also supports easy modification function. The YEDDA system also supports the simple system recommendation function to automatically annotate the data. You can refer our ACL 2018 demo paper for more information, this paper is nominated as the best demo in ACL 2018.

Kiwisher commented 5 years ago

I got it. Thx for your help~