We present ongoing work dealing with a Linked Data compliant representation of infrastructures using wordnets for connecting multilingual Sign Language data sets.We build for this on already existing RDF and OntoLex representations of Open Multilingual Wordnet (OMW) data sets and work done by the European EAS-IER research project on the use of the CSV files of OMW for linking glosses and basic semantic information associated with Sign Language data sets in two languages: German and Greek.In this context, we started the transformation into RDF of a Danish data set, which links Danish Sign Language data and the wordnet for Danish, DanNet.The final objective of our work is to include Sign Language data sets (and their conceptual cross-linking via wordnets) in the Linguistic Linked Open Data cloud.

For Sign Languages (SLs), can we create a SignNet, like a WordNet for spoken languages: a network of semantic relations between constitutive elements of SLs?We first discuss approaches that link SL data to wordnets, or integrate such elements with some adaptations into the structure of WordNet.Then, we present requirements for a SignNet, which is built on SL data and then linked to WordNet.

This paper describes ongoing work aiming at adding pronunciation information to lexical semantic resources, with a focus on open wordnets. Our goal is not only to add a new modality to those semantic networks, but also to mark heteronyms listed in them with the pronunciation information associated with their different meanings. This work could contribute in the longer term to the disambiguation of multi-modal resources, which are combining text and speech.

In this paper we describe our current work on representing a recently created German lexical semantics resource in OntoLex-Lemon and in conformance with Word-Net specifications.Besides presenting the representation effort, we show the utilization of OntoLex-Lemon to bridge from WordNet-like resources to full lexical descriptions and extend the coverage of WordNets to other types of lexical data, such as decomposition results, exemplified for German data, and inflectional phenomena, here outlined for English data.

In the context of a student software project we are investigating the use of Word-Net for improving the automatic detection and classification of actors (or characters) mentioned in folktales.Our starting point is the book "Classification of International Folktales", out of which we extract text segments that name the different actors involved in tales, taking advantage of patterns used by its author, Hans-Jörg Uther.We apply on those text segments functions that are implemented in the NLTK interface to WordNet in order to obtain lexical semantic information to enrich the original naming of characters proposed in the "Classification of International Folktales" and to support their translation in other languages.