Language to Logical Form with Neural Attention

Understand

Semantic parsing aims at mapping natural language to machine interpretable meaning representations.

• Traditional approaches rely on high-quality lexicons, manually-built templates, and linguistic features which are either domain- or representation-specific.
• In this paper we present a general method based on an attention-enhanced encoder-decoder model.
• We encode input utterances into vector representations, and generate their logical forms by conditioning the output sequences or trees on the encoding vectors.