Existing learning algorithms have primarily focused on building actionable meaning representations which can, for example, directly query a database (Liang et al., 2011;Kwiatkowski et al., 2013) or instruct a robotic agent (Chen, 2012;Artzi and Zettlemoyer, 2013b).
due to their end-to-end nature, such models must be relearned for each new target application and have only been used to parse restricted styles of text, such as questions and imperatives.