| Abstract | Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of the target logical forms . |
| Abstract | In this paper, we learn to map questions to answers via latent logical forms , which are induced automatically from question-answer pairs. |
| Abstract | In tackling this challenging learning problem, we introduce a new semantic representation which highlights a parallel between dependency syntax and efficient evaluation of logical forms . |
| Introduction | Answering these types of complex questions compositionally involves first mapping the questions into logical forms (semantic parsing). |
| Introduction | Supervised semantic parsers (Zelle and Mooney, 1996; Tang and Mooney, 2001; Ge and Mooney, 2005; Zettlemoyer and Collins, 2005; Kate and Mooney, 2007; Zettlemoyer and Collins, 2007; Wong and Mooney, 2007; Kwiatkowski et al., 2010) rely on manual annotation of logical forms , which is expensive. |
| Introduction | (2010), we obviate the need for annotated logical forms by considering the end-to-end problem of mapping questions to answers. |