Build status codecov

A framework for building semantic parsers (including neural module networks) with AllenNLP, built by the authors of AllenNLP

Supported datasets

Supported models


Coming sometime in the future... You can look at this old tutorial, but the part about using NLTK to define a grammar is outdated. Now you can use DomainLanguage to define a python executor, and we analyze the type annotations in the functions in that executor to automatically infer a grammar for you. It is much easier to use than it used to be. Until we get around to writing a better tutorial for this, the best way to get started using this is to look at some examples. The simplest is the Arithmetic language in the DomainLanguage test (there's also a bit of description in the DomainLanguage docstring). After looking at those, you can look at more complex (real) examples in the domain_languages module. Note that the executor you define can have learned parameters, making it a neural module network. The best place to get an example of that is currently this unfinished implementation of N2NMNs on the CLEVR dataset. We'll have more examples of doing this in the not-too-distant future.