Simple, Fast Semantic Parsing with a Tensor Kernel
We describe a simple approach to semantic parsing based on a tensor product kernel. We extract two feature vectors: one for the query and one for each candidate logical form. We then train a classifier using the tensor product of the two vectors. Using very simple features for both, our system achieves an average F1 score of 40.1 more complex systems but is simpler to implement and runs faster.
READ FULL TEXT