WSD for subcategorization acquisition task description

Subcategorization Acquisition as an Evaluation Method for WSD

Evaluation of word sense disambiguation (WSD) systems is often based on machine-readable dictionaries (MRDs). Such evaluation typically employs a set of fine-grained dictionary senses and considers them all to be equally important. In this paper, we propose a novel evaluation method for WSD systems in the context of automatic subcategorization acquisition. Building on an extant subcategorizatio...

Probabilistic word sense disambiguation : Analysis and techniques for combining knowledge sources

This thesis shows that probabilistic word sense disambiguation systems based on established statistical methods are strong competitors to current state-of-the-art word sense disambiguation (WSD) systems. We begin with a survey of approaches to WSD, and examine their performance in the systems submitted to the Senseval-2 WSD evaluation exercise. We discuss existing resources for WSD, and investi...

Improving Subcategorization Acquisition with WSD

Using Parallel Texts and Lexicons for Verbal Word Sense Disambiguation

We present a system for verbal Word Sense Disambiguation (WSD) that is able to exploit additional information from parallel texts and lexicons. It is an extension of our previous WSD method (Dušek et al., 2014), which gave promising results but used only monolingual features. In the follow-up work described here, we have explored two additional ideas: using English-Czech bilingual resources (as...

Using Verb Subcategorization for Word Sense Disambiguation

We develop a model for predicting verb sense from subcategorization information and integrate it into SSI-Dijkstra, a wide-coverage knowledge-based WSD algorithm. Adding syntactic knowledge in this way should correct the current poor performance of WSD systems on verbs. This paper also presents, for the first time, an evaluation of SSI-Dijkstra on a standard data set which enables a comparison ...