I am trying to implement a probabilistic ccg with lambda-calculus features.
Basically i want to do the following code:
>> lex = parseLexicon(r'''
:- S,NP
He => NP {sem=\x.he(x)} [1.0]
Walks => S\NP {sem=\X. walk(X)} [1.0]
There => S\S {sem=\x . there(x)} [1.0]
''')
>> parser = CCGChartParser(lex)
>> all_parses = parser.nbest_parse(“He walks
there”.split(),n=100)
>> for parse in all_parses:
printCCGDerivation(parse)
but existing CCG implementation of NLTK does not support {sem=\x.he(x)} [1.0] kinds of semantic parts in lexicon.
Are there Any other CCG implementations that can handle this? Or can i represent this inside of NLTK?