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View Code? Open in Web Editor NEWAn Adaptor Grammar model implementation in Python.
An Adaptor Grammar model implementation in Python.
While using test_launch, how can I obtain the parse tree for a given test sentence? Currently, no parse tree as such is provided. Also, it will be helpful if you can show, how to calculate the probability/confidence of the obtained parse tree?
Hi once the model is genenrated, how do we evaluate the model? What would be object attributes that I can use to access elements in the pickle file.
Hi Ke! I am very excited about your toolbox, however I unfortunately do not get it to work for the collocation grammar. Everything works fine for the unigram grammar. I have tried using the input (train.dat/test.dat) that you provided and get an assertion error in hybrid.py:
line 1333, in model_state_assertion adapted_production_dependent[adapted_production]))
AssertionError: : Word -> a (Word -> Chars, Chars -> Char, Char -> 'a')
: 0 set()
: 5 {Collocation -> i ' l l p u t i t a w a y (Collocation -> Words, Words -> Word Words, Word -> i ' l l p u (Word -> Chars, Chars -> Char Chars, Char -> ...
Unfortunately, I could not figure out how to solve it. Do you maybe have a solution?
Thank you very much for your help in advance!
Best regards,
Lena
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