We explore a stacked framework for learning to predict dependency structures for natural language sentences. A typical approach in graph-based dependency parsing has been to assume a factorized model, where local features are used but a global function is optimized (McDonald et al., 2005b). Recently Nivre and McDonald (2008) used the output of one dependency parser to provide features for anoth...

We present our work on semi-supervised parsing of natural language sentences, focusing on multi-source crosslingual transfer of delexicalized dependency parsers. We first evaluate the influence of treebank annotation styles on parsing performance, focusing on adposition attachment style. Then, we present KLcpos3 , an empirical language similarity measure, designed and tuned for source parser we...

Information theoretic measures of incremental parser load were generated from a phrase structure parser and a dependency parser and then compared with incremental eye movement metrics collected for the same temporarily syntactically ambiguous sentences, focussing on the disambiguating word. The findings show that the surprisal and entropy reduction metrics computed over a phrase structure gramm...

Following Kiperwasser and Goldberg (2016), we present a multilingual dependency parser with a bidirectionalLSTM (BiLSTM) feature extractor and a multi-layer perceptron (MLP) classifier. We trained our transition-based projective parser in UD version 2.0 datasets without any additional data. The parser is fast, lightweight and effective on big treebanks. In the CoNLL 2017 Shared Task: Multilingu...

If all we want from a syntactic parser is a dependency tree, what do we gain by first computing a different representation such as a phrase structure tree? The principle of parsimony suggests that a simpler model should be preferred over a more complex model, all other things being equal, and the simplest model is arguably one that maps a sentence directly to a dependency tree – a bare-bones de...

Compared to the prosody study in statement-like sentence, little research has been conducted in interrogative sentence, which will definitely improve the naturalness of spoken dialog system. This paper proposes a computational model to assign stress in interrogative sentences using linguistic knowledge. We firstly investigate the interrogative sentences perceptually to label their stress locati...

If all we want from a syntactic parser is a dependency tree, what do we gain by first computing a different representation such as a phrase structure tree? The principle of parsimony suggests that a simpler model should be preferred over a more complex model, all other things being equal, and the simplest model is arguably one that maps a sentence directly to a dependency tree – a bare-bones de...

We present and implement a fourth-order projective dependency parsing algorithm that effectively utilizes both “grand-sibling” style and “tri-sibling” style interactions of third-order and “grand-tri-sibling” style interactions of forth-order factored parts for performance enhancement. This algorithm requires O(n5) time and O(n4) space. We implement and evaluate the parser on two languages—Engl...

This paper proposes an approach to enhance dependency parsing in a language by using a translated treebank from another language. A simple statistical machine translation method, word-by-word decoding, where not a parallel corpus but a bilingual lexicon is necessary, is adopted for the treebank translation. Using an ensemble method, the key information extracted from word pairs with dependency ...

The 200 million word corpus of the Bank of English was annotated morphologically and syntactically using the English Constraint Grammar analyser, a rulebased shallow parser developed at the Research Unit for Computational Linguistics, University of Helsinki. We discuss the annotation system and methods used in the corpus work, as well as the theoretical assumptions of the Constraint Grammar syn...