Despite the recent success of deep neural networks in natural language processing and
other spheres of artificial intelligence, their interpretability remains a challenge. We analyze …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

This article describes a number of log-linear parsing models for an automatically extracted
lexicalized grammar. The models are “full” parsing models in the sense that probabilities are …

The statistical modelling of language, together with advances in wide-coverage grammar
development, have led to high levels of robustness and efficiency in NLP systems and made …

Dependency grammar and dependency parsing Page 1 Dependency grammar and
dependency parsing Syntactic analysis (5LN455) 2012-12-11 Joakim Nivre Department of …

Machine learning based on various forms of inductive inference has been used for a wide
range of problems in natural language processing, with syntactic parsing being one of the …

This paper describes and evaluates log-linear parsing models for Combinatory Categorial
Grammar (CCG). A parallel implementation of the L-BFGS optimisation algorithm is …

This paper shows how to construct semantic representations from the derivations produced
by a wide-coverage CCG parser. Unlike the dependency structures returned by the parser …

Probabilistic modeling of lexicalized grammars is difficult because these grammars exploit
complicated data structures, such as typed feature structures. This prevents us from applying …

Recent work on supertagging using a feedforward neural network achieved significant
improvements for CCG supertagging and parsing (Lewis and Steedman, 2014). However …