We analyze how different conceptions of lexical semantics affect sense annotations and how multiple sense inventories can be compared empirically, based on annotated text. Our study focuses on the MASC project, where data has been annotated using WordNet sense identifiers on the one hand, and FrameNet lexical units on the other. This allows us to compare the sense inventories of these lexical r...

Like most natural language disambiguation tasks, word sense disambiguation (WSD) requires world knowledge for accurate predictions. Several proxies for this knowledge have been investigated, including labeled corpora, user-contributed knowledge, and machine readable dictionaries, but each of these proxies requires significant manual effort to create, and they do not cover all of the ambiguous t...

This paper presents few extensions to the logic form representation and a method for transforming WordNet glosses into logic forms using a set of high-precision rules combined with a set of high recall heuristics. An almost 3% increase in POS tagging accuracy is achieved over state-of-the art results at the expense of user intervention on only 7.52% of words. We apply a nearest neighbor solutio...

This article investigates how the signaling-mode of electronic glosses in online texts (i.e., presented digitally on a computer screen) influences the user's reading process, incidental vocabulary learning, and text comprehension. Indeed, does the fact that hyperlinks with dictionary definitions are visible (i.e., highlighted) or invisible affect the foreign language learner's look-up behaviour...

In this paper we present a progress report of the OntoWordNet project, a research program aimed at achieving a formal specification of WordNet. Within this program, we developed a hybrid bottom-up top-down methodology to automatically extract association relations from WordNet, and to interpret those associations in terms of a set of conceptual relations, formally defined in the DOLCE foundatio...

2 Abbreviations used in the glosses: dem = demonstrative pronoun, n = neuter, nn = nonneuter, sg = singular, pl = plural, inv = inversion form, pcple = past participle.