Semantic parsing is the task of mapping natural language sentences to complete formal meaning representations. The performance of semantic parsing can be potentially improved by u...
Discriminative reranking has been able to significantly improve parsing performance, and co-training has proven to be an effective weakly supervised learning algorithm to bootstr...
We present a novel approach to parse web search queries for the purpose of automatic tagging of the queries. We will define a set of probabilistic context-free rules, which genera...
Conventional n-best reranking techniques often suffer from the limited scope of the nbest list, which rules out many potentially good alternatives. We instead propose forest reran...
This paper considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of candidate parses for each input sentence, with assoc...