A great deal of psycholinguistic findings reveal that context highlights or obscures certain aspects in the meaning of a word (viz., word sense modulation). Computational models of lexicon, however, are mostly concerned with the ways context selects a meaning for a word (word sense selection). In this paper, we propose a model that combines sense selection with sense modulation. Word senses in ...

Dutch allows for variation as to whether the first position in the sentence is occupied by the subject or by some other constituent, such as the direct object. In particular situations, however, this commonly observed variation in word order is 'frozen' and only the subject appears in first position. We hypothesize that this partial freezing of word order in Dutch can be explained from the depe...

There have been some works that learn a lexicon together with the corpus to improve the word embeddings. However, they either model the lexicon separately but update the neural networks for both the corpus and the lexicon by the same likelihood, or minimize the distance between all of the synonym pairs in the lexicon. Such methods do not consider the relatedness and difference of the corpus and...

In participating in this evaluation campaign, our first objective is to analyze the retrieval effectiveness when using TEL (The European Library) corpora composed of very short descriptions (library catalogue records) and to evaluate the retrieval effectiveness of several IR models. As a second objective we want to design and evaluate a stopword list and a light stemming strategy for the Persia...

Supervised word sense disambiguation requires training corpora that have been tagged with word senses, which begs the question of which word senses to tag with. The default choice has been WordNet, with its broad coverage and easy accessibility. However, concerns have been raised about the appropriateness of its fine-grained word senses for WSD. WSD systems have been far more successful in dist...

Amazon Mechanical Turk (MTurk) is a marketplace for so-called “human intelligence tasks” (HITs), or tasks that are easy for humans but currently difficult for automated processes. Providers upload tasks to MTurk which workers then complete. Natural language annotation is one such human intelligence task. In this paper, we investigate using MTurk to collect annotations for Subjectivity Word Sens...

We report a series of event-related potential experiments designed to dissociate the functionally distinct processes involved in the comprehension of highly restricted lexical-semantic relations (antonyms). We sought to differentiate between influences of semantic relatedness (which are independent of the experimental setting) and processes related to predictability (which differ as a function ...

A probabilistic method is used for word sense disambiguation where the features taken are the surrounding six words. As their surface forms are used, no syntactic or semantic analysis is required. Despite its simplicity, this method is able to disambiguate the noun interest accurately. Using the common data set of (Bruce & Wiebe 94), we have obtained an average accuracy of 86.6% compared with t...

This study aimed at investigating the effect of visual (Cuisenaire Rods) and auditory nonsensical monosyllables using Pratt speech processing software as teaching techniques on retention of word stress. To this end, 60 high school participants made the two experimental groups of the study each having 30 students on the basis of their proficiency scores on KET (Key English Test). In one experime...

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