[PDF] Top 20 A Bayesian Model for Unsupervised Semantic Parsing

... supervised semantic parsing and propose a Bayesian non-parametric approach which uses hierarchical Pitman-Yor (PY) processes (Pitman, 2002) to model statistical dependencies between predicate ... See full document

... present a system which learns narrative chains from newswire texts. Relevant phrases are iden- tified based on shared protagonists. The phrases are clustered into equivalence classes and tempo- rally ordered using a ... See full document

... the unsupervised model only correctly predicted transitive verbs 20% of the time and ad- verbs 39% of the ...correct parsing decisions also lead to improved performance across many other cat- egories ... See full document

... coupled model outperforms the factored version, and that reducing the argu- ment filler sparsity with clustering also has a sub- stantial positive ...(e.g., semantic roles for adverbials do not normally ... See full document

... in unsupervised parsers that optimize se- mantically oriented objectives, typically us- ing reinforcement ...their model lacks interpretability as it is not grounded in parsing ...to ... See full document

... many semantic pars- ing systems resemble the formalism, each was pro- posed as an independent model requiring custom al- gorithms, leaving it unclear how developments in one line of inquiry relate to ...tic ... See full document

... POSLDA model has pushed stopwords to their own func- tion classes (rather than content) freeing us from having to perform pre- or post-processing steps to ensure interpretable ... See full document

... first unsupervised approach for this task. Our model compensates for the lack of training data by employing a self training protocol based on identifying high confi- dence self labeled examples and using ... See full document

... to semantic parsing is syn- tactic variations of the same meaning, which abound in natural ...Supervised semantic parsing addresses this issue by learning to construct the grammar automati- ... See full document

... Unsupervised semantic parsing was first proposed by Poon & Domingos (2009, 2010) with their USP ...probabilistic model over the dependency tree and semantic parse us- ing Markov ... See full document

... Different ratios To investigate the efficiency of our method in semi-supervised learning, we vary the ratio of labeled data kept on ATIS from 1% to 90%. In Figure 3, we can see that dual learning strategy enhances ... See full document

... Another approach to adaptation is to favor training examples that are similar to the target. We first mod- ified the weight given by the parser to each training sentence based on the similarity of the sentence to target ... See full document

... Following the experimental setup of Jia and Liang (2016): we use 200 hidden units and 100- dimensional word vectors for sentence encoding. The dimensions of action embedding are tuned on validation datasets for each ... See full document

... In order to enforce structural consistency, most existing work applies different types of structural constraints during inference. The inference prob- lem are typically solved via Integer Linear Pro- gramming (ILP) ... See full document

... Brown Clusters. Clustering groups of similar words together provides a way of generalizing them. In this work, we explore the use of Brown clusters (Brown et al., 1992) in both feature vec- tors and tree kernels. The ... See full document

... The adjacency property described in the previous section makes shortest common cover link sets es- pecially suitable for incremental parsing. Consider the example given in figure 2. When the word the is read, the ... See full document

... dependency parsing aims to learn a dependency grammar from text anno- tated with only POS ...to unsupervised dependen- cy parsing that uses a neural model to predict grammar rule probabilities ... See full document

... Syntactic parsing contributes crucially to the overall performance of the joint parsing by pro- viding a solid basis for further semantic ...dependency parsing can be more in- fluential than ... See full document

... We model the spatial information in a unified Markov Network, where the phase for location i at each time is not only dependent upon its previous phase, but its ...Linear Model is used to integrate the ... See full document

... Yejin Choi and Claire Cardie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 590 Generating High-Coverage Semantic Orientation Lexicons From ... See full document