Paper: Semantic Parsing on Freebase from Question-Answer Pairs

ACL ID D13-1160
Title Semantic Parsing on Freebase from Question-Answer Pairs
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

In this paper, we train a semantic parser that scales up to Freebase. Instead of relying on annotated logical forms, which is especially expensive to obtain at large scale, we learn from question-answer pairs. The main chal- lenge in this setting is narrowing down the huge number of possible logical predicates for a given question. We tackle this problem in two ways: First, we build a coarse mapping from phrases to predicates using a knowledge base and a large text corpus. Second, we use a bridging operation to generate additional predicates based on neighboring predicates. On the dataset of Cai and Yates (2013), despite not having annotated logical forms, our sys- tem outperforms their state-of-the-art parser. Additionally, we collected a more realistic and challenging dataset of question...