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The Practitioner's Cookbook for Linked Lexical Resources


There is a big demand for lexical-semantic resources in Natural Language Processing to improve the performance of language processing, such as word sense disambiguation and Information Extraction. This demand is not met by single resources, neither by expert-constructed resources, such as WordNet and FrameNet, nor by collaboratively constructed resources, such as Wikipedia and Wiktionary. Previously, this bottleneck has been addressed by projects on linking lexical resources at the word sense level in order to increase their coverage and enrich sense representations. More recently, methods for the automatic linking of lexical resources at the sense level (as opposed to manual linking) are being developed. This has to go hand in hand with a harmonization or even standardization of the lexical resources at the representation level.

This tutorial is intended to convey a fundamental understanding of the emerging field of linked lexical resources. The first part of the tutorial will consider linking of lexical resources and the foundations of collaboratively constructed resources. It will start by characterizing the task of linking lexical resources at the word sense level. Then, we will introduce the collaboratively constructed lexical-semantic resources based on Wikipedia and Wiktionary. Thirdly, a method for automatic linking of lexical resources will be presented and illustrated by the automatic word sense alignment of Wiktionary and WordNet.

The second part will focus on a large-scale example of a linked lexical resource and its use in language processing, UBY. First, we will show how the standardized format of UBY can be used for the automatic linking of verb senses. Then, we will demonstrate the practical use of UBY for language processing by considering knowledge-based word sense disambiguation as a use case. Detailed examples of accessing different resources and information types will be presented. In particular, we will explain how to exploit the sense links between resources for word sense disambiguation.


Judith Eckle-Kohler, Iryna Gurevych

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