关于 CNN_BILSTM_CRF model的一些问题 about ncrfpp HOT 8 CLOSED

1. Character CNN/LSTM是可以和自定义feature一起用的，不冲突。
   2.你是对的，如果不用某个feature，你的输入文件里面就不需要那一列。并不是所有的都需要的。

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one more question，in the file named demo.train.config ,there are some Hyperparameters:
cnn_layer=4
char_hidden_dim=30
I can't really uderstand what those 2 parameters means, do you mind explain it? Thanks

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You may refer the configuration explanation here: https://github.com/jiesutd/NCRFpp/blob/master/readme/Configuration.md

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thank you .this file I have read already , so I JUST want to make it sure, if I use lstm as word-sequence layer,
cnn_layer is useless and can be annotated, and the parameter of char_hidden_dim=50 means the feature i extract from word and dim is 50 ,and than joint it after word2vec and pos_vec?

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Do you mean "ignored" rather than "annotated"? Yes, if you choose the LSTM to encode the word sequence then the settings of CNN can be ignored.

About the char_hidden_dim=50:
"the feature i extract from word and dim is 50", this is right.
"joint it after word2vec and pos_vec", it is concatenated with word embeddings(not word2vec) and feature embeddings.

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if I SET char_emb_dim=100 (this parameter in I/O part)
char_hidden_dim=50(this parameter in Hyperparameters part)
is that means i input the pretrained char_embedding which in 100 dim ,and after cnn_char_layer I GET char_features_embdding in 50dim?and it can concatenate with word embedding?

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exactly.

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thank you very much!

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