In this paper, we introduce the Lefff, a freely available, accurate and large-coverage
morphological and syntactic lexicon for French, used in many NLP tools such as large …

This paper presents a simple yet effective semi-supervised method to improve Chinese word
segmentation and POS tagging. We introduce novel features derived from large auto …

This paper presents a simple and effective approach to improve dependency parsing by
using subtrees from auto-parsed data. First, we use a baseline parser to parse large-scale …

Het doel van de computationele taalkunde is het maken van systemen die in staat zijn
natuurlijke taal te begrijpen en te produceren, net zoals wij mensen dat doen. Het maken …

In this paper, we present a novel approach which incorporates the web-derived selectional
preferences to improve statistical dependency parsing. Conventional selectional preference …

The accuracy of parsing has exceeded 90% recently, but this is not high enough to use
parsing results practically in natural language processing (NLP) applications such as …

One of the goals of the LASSY STEVIN project (Large Scale Syntactic Annotation of written
Dutch) is a syntactically annotated (manually verified) corpus of 1 million words. In addition …

Prepostitional phrase (PP) attachment is a well known challenge to parsing. In this paper,
we combine the insights of different works, namely:(1) treating PP attachment as a …

In this work, we present a data-driven method to enhance syntax trees with additional
dependencies as defined in the wellknown Stanford Dependencies scheme, so as to give …

In the past decade several parsing systems for natural language have emerged, which use
different methods and formalisms. For instance, systems that employ a handcrafted grammar …