We investigated the internal structure of words in the mental lexicon by using a crossword puzzle paradigm. In two experiments, subjects were presented with word fragments along with a semantic cue, and were asked to retrieve the whole word that contained the pre· sented fragment and was compatible with the semantic information. In Experiment 1, we found that any cluster of adjacent three lette...

This paper describes a heuristic approach capable of automatically clustering senses in a machinereadable dictionary (MRD). Including these clusters in the MRD-based lexical database offers several positive benefits for word sense disambiguation (WSD). First, the clusters can be used as a coarser sense division, so unnecessarily fine sense distinction can be avoided. The clustered entries in th...

We present a novel approach to the automatic acquisition of a Verbnet like classification of French verbs which involves the use (i) of a neural clustering method which associates clusters with features, (ii) of several supervised and unsupervised evaluation metrics and (iii) of various existing syntactic and semantic lexical resources. We evaluate our approach on an established test set and sh...

This paper addresses ways in which we envisage to reduce the fine-grainedness of WordNet and express in a more systematic way the relations between its numerous sense distinctions. In the EuroWordNet project, we have distinguished various automatic methods for grouping senses into more coarse-grained sense groups. These resulting clusters reflect aspects of lexical organization, displaying a va...

this article studies the generative grammar approach and some other theories driven from it to lexicon and lexical entries. generative grammar is known as a syntax-based theory, so some aspects of language which have been studied in this theory may have been ignored in other theories. this article shows that more attention has been given to lexicon and lexical entries since 50s. we may claim th...

In this paper we present a new method for measuring semantic relatedness of lexical units, which can be used to generate a thesaurus automatically. The method is based on a comparison of probability distributions of semantic frames generated using the LDA-frames algorithm. The idea is evaluated by measuring the overlap of WordNet synsets and generated semantic clusters. The results show that th...

The present study investigated the effect of different types of text simplification (i.e., reducing the lexical and syntactic complexity of texts) on reading comprehension of English as a Foreign Language learners (EFL). Sixty female intermediate EFL learners from three intact classes in Tabarestan Language Institute in Tehran participated in the study. The intact classes were assigned to three...

SenseClusters is a freely available system that identifies similar contexts in text. It relies on lexical features to build first and second order representations of contexts, which are then clustered using unsupervised methods. It was originally developed to discriminate among contexts centered around a given target word, but can now be applied more generally. It also supports methods that cre...

We present experiments aiming at an automatic classification of Spanish verbs into lexical semantic classes. We apply well-known techniques that have been developed for the English language to Spanish, proving that empirical methods can be re-used through languages without substantial changes in the methodology. Our results on subcategorisation acquisition compare favourably to the state of the...