Arc-Standard Spinal Parsing with Stack-LSTMs

We present a neural transition-based parser for spinal trees, a dependency representation of constituent trees. The parser uses Stack-LSTMs that compose constituent nodes with dependency-based derivations. In experiments, we show that this model adapts to different styles of dependency relations, but this choice has little effect for predicting constituent structure, suggesting that LSTMs induce useful states by themselves.Comment: IWPT 201

Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing

Latent tree learning models represent sentences by composing their words according to an induced parse tree, all based on a downstream task. These models often outperform baselines which use (externally provided) syntax trees to drive the composition order. This work contributes (a) a new latent tree learning model based on shift-reduce parsing, with competitive downstream performance and non-trivial induced trees, and (b) an analysis of the trees learned by our shift-reduce model and by a chart-based model.Comment: ACL 2018 workshop on Relevance of Linguistic Structure in Neural Architectures for NL

ProphetMT: controlled language authoring aid system description

This paper presents ProphetMT, a monolingual Controlled Language (CL) authoring tool which allows users to easily compose an in-domain sentence with the help of tree-based SMT-driven auto-suggestions. The interface also visualizes target-language sentences as they are built by the SMT system. When the user is finished composing, the final translation(s) are generated by a tree-based SMT system using the text and structural information provided by the user. With this domain-specific controlled language, ProphetMT will produce highly reliable translations. The contributions of this work are: 1) we develop a user-friendly auto-completion-based editor which guarantees that the vocabulary and grammar chosen by a user are compatible with a tree-based SMT model; 2) by applying a shift-reduce-like parsing feature, this editor allows users to write from left-to-right and generates the parsing results on the fly. Accordingly, with this in-domain composing restriction as well as the gold-standard parsing result, a highly reliable translation can be generated