Comments (4)
Hi,
There are two ways you can do this.
Since the NER model uses only the words and the NER labels in the data, one way is to convert your format to match the original format by filling the POS and Chunking columns with any symbols you like.
Another way is to write a new Reader to handle your format.
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I see. Assigning "None" to pos, chunk and ner variables in create_alphabets
isn't enough? This way won't be any real assignment to such values. Or I guess I will insert "_" chars in my database, so I can create two more columns to match the current code.
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from neuronlp2.
Ok, so I will try that. Thanks!
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Related Issues (20)
- RuntimeError: maximum recursion depth exceeded (python3+torch0.4) HOT 4
- TypeError: invalid file: None ===conllx_stacked_data.create_alphabets(alphabet_path, None,
- No such file or directory: 'data/sskip/sskip.ger.64.gz' && data/sskip/sskip.eng.100.gz && data/conll2003/english/eng.train.bioes.conll HOT 3
- whart is /run_analyze.sh used for, looks missing some files HOT 1
- Time to Compute
- Run a trained model HOT 1
- RuntimeError: maximum recursion depth exceeded HOT 2
- some questions about dataset and f1 score! HOT 1
- Can you give me the data and sskip.eng.100.gz? HOT 2
- Error Analysis
- how to use Elmo or Bert HOT 1
- embedding size HOT 1
- parsing input format HOT 3
- variability in the results HOT 2
- RuntimeError: CUDA error: an illegal instruction was encountered HOT 3
- Interpretation of code variables HOT 2
- Error trying to train a model HOT 2
- AssertionError for word_dim HOT 2
- Unable to find training data HOT 2
- TypeError in Biaffine HOT 1
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