Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
Harnessing the statistical power of neural networks to perform language understanding and symbolic reasoning is difficult, when it requires executing efficient discrete operations against a large knowledge-base. In this work, we introduce a Neural Symbolic Machine, which contains (a) a neural “programmer”, i.e., a sequence-to-sequence model that maps language utterances …