Broad-coverage language resources which provide prior linguistic knowledge must improve the accuracy and the performance of NLP applications. We are constructing a broad-coverage lexical resource to improve the accuracy of morphological analyzers and part-of-speech taggers of Arabic text. Over the past 1200 years, many different kinds of Arabic language lexicons were constructed; these lexicons...

The last two decades have seen the development of various semantic lexical resources such as WordNet (Miller, 1995) and the USAS semantic lexicon (Rayson et al., 2004), which have played an important role in the areas of natural language processing and corpus-based studies. Recently, increasing efforts have been devoted to extending the semantic frameworks of existing lexical knowledge resource...

We introduce a new approach for manually constructing broad-coverage lexical ressources based on a specific type of lexical network called lexical system. Drawing on experience gained from the construction of the French Lexical Network (fr-LN), we begin by formally characterizing lexical systems as “small-world” graphs of lexical units that are primarily organized around the system of Meaning-T...

Most attempts to integrate FrameNet in NLP systems have so far failed because of its limited coverage. In this paper, we investigate the applicability of distributional and WordNetbased models on the task of lexical unit induction, i.e. the expansion of FrameNet with new lexical units. Experimental results show that our distributional and WordNet-based models achieve good level of accuracy and ...

This report investigates issues of lexical coverage in Indian languages. More specifically, a parallel analysis of Out-of-Vocabulary words is made in Telugu and Tamil. Although generic, this study is focussed on understanding the morphological aspects in these languages as necessary for speech recognition. The observations reveal that morphological analysis and preprocessing can increase the le...

a r t i c l e i n f o a b s t r a c t We present an automatic approach to the construction of BabelNet, a very large, wide-coverage multilingual semantic network. Key to our approach is the integration of lexicographic and encyclopedic knowledge from WordNet and Wikipedia. In addition, Machine Translation is applied to enrich the resource with lexical information for all languages. We first con...

We report on results of combining graphical modeling techniques with Information Extraction resources (Pattern Dictionary and Lexicon) for both frame and semantic role assignment. Our approach demonstrates the use of two human built knowledge bases (WordNet and FrameNet) for the task of semantic extraction.

This paper describes an approach to providing lexical information for natural language processing in unrestricted domains. A system of approximately 1200 morphological rules is used to extend a core lexicon of 39,000 words to provide lexical coverage that exceeds that of a lexicon of 80,000 words or 150,000 word forms. The morphological system is described, and lexical coverage is evaluated for...

Information about the lexical capacity of the speakers of a specific language is indispensible for empirical and experimental studies on the human behavior of using speech as a communicative means. Unlike the increasing number of gigantic textor web-based corpora that have been developed in recent decades, publicly distributed spoken resources, espcially conversations, are few in number. This a...