English. Dependency parsing is an important component in information extraction, in particular when using suitable formalisms and accurate and efficient parsing techniques. We review recent advances in dependency parsing and describe our own contribution in the context of the Evalita 2014 DPIE task. Italiano. Il parsing a dipendenze è un componente importante nell’estrazione di informazione da ...

This paper describes an algorithm for accelerating the CFG-parsing process by using dependency (or modiier-modiiee relationship) information given by, for instance, dependency estimation programs such as stochastic parsers, user's indication in an interactive application, and linguistic annotations added in a source text. This is a method for enhancing existing grammar-based CFG-parsing system ...

The Evalita ’07 Parsing Task has been the first contest among parsing systems for Italian. It is the first attempt to compare the approaches and the results of the existing parsing systems specific for this language using a common treebank annotated using both a dependency and a constituency-based format. The development data set for this parsing competition was taken from the Turin University ...

In applying word-based dependency parsing such as Universal Dependencies (UD) to Japanese, the uncertainty of word segmentation emerges for defining a word unit of the dependencies. We introduce the following hierarchical word structures to dependency parsing in Japanese: morphological units (a short unit word, SUW) and syntactic units (a long unit word, LUW). This paper describes the results o...

Dependency parsers are critical components within many NLP systems. However, currently available dependency parsers each exhibit at least one of several weaknesses, including high running time, limited accuracy, vague dependency labels, and lack of nonprojectivity support. Furthermore, no commonly used parser provides additional shallow semantic interpretation, such as preposition sense disambi...

Derivations under different grammar formalisms allow extraction of various dependency structures. Particularly, bilexical deep dependency structures beyond surface tree representation can be derived from linguistic analysis grounded by CCG, LFG, and HPSG. Traditionally, these dependency structures are obtained as a by-product of grammar-guided parsers. In this article, we study the alternative ...

This paper describes the dependency parser we used in the NLP Tools Contest, 2009 for parsing Hindi, Bangla and Telugu. The parser uses a bidirectional parsing algorithm with two operations proj and non-proj to build the dependency tree. The parser obtained Labeled Attachment Score of 71.63%, 59.86% and 67.74% for Hindi, Telugu and Bangla respectively on the treebank with fine-grained dependenc...

Unsupervised dependency parsing is one of the most challenging tasks in natural languages processing. The task involves finding the best possible dependency trees from raw sentences without getting any aid from annotated data. In this paper, we illustrate that by applying a supervised incremental parsing model to unsupervised parsing; parsing with a linear time complexity will be faster than th...

We propose the first joint model for word segmentation, POS tagging, and dependency parsing for Chinese. Based on an extension of the incremental joint model for POS tagging and dependency parsing (Hatori et al., 2011), we propose an efficient character-based decoding method that can combine features from state-of-the-art segmentation, POS tagging, and dependency parsing models. We also describ...

This paper describes the characteristic features of dependency structures of Japanese spoken language by investigating a spoken dialogue corpus, and proposes a stochastic approach to dependency parsing. The method can robustly cope with inversion phenomena and bunsetsus which don’t have the head bunsetsu by relaxing the syntactic dependency constraints. The method acquires in advance the probab...