Semantic Parsing in Limited Resource Conditions

Semantic parsing has revolutionized the field of human-machine interaction by adeptly translating natural language utterances into machine-readable representations. Despite this advancement, the development of robust semantic parsers frequently encounters difficulties due to the scarcity of data and computational resources. This thesis aims to improve existing semantic parsing techniques to ensure their effectiveness in resource-constrained conditions.