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Statistical methods to extract translational equivalents from non-parallel corpora hold the promise of ensuring the required coverage and domain customisation of lexicons as well as accelerating their compilation and maintenance. A challenge for these methods are rare, less common words and expressions, which often have low corpus frequencies. However, it(More)
The paper examines different possibilities to take advantage of the taxonomic organization of a thesaurus to improve the accuracy of classifying new words into its classes. The results of the study demonstrate that taxonomic similarity between nearest neighbors, in addition to their dis-tributional similarity to the new word, may be useful evidence on which(More)
The study addresses the problem of automatic acquisition of entailment relations between verbs. While this task has much in common with paraphrases acquisition which aims to discover semantic equivalence between verbs, the main challenge of entailment acquisition is to capture asymmetric, or directional, relations. Motivated by the intuition that it often(More)
In automatic summarisation it was noticed that knowledge poor methods do not necessary preform worse than those which employ several knowledge sources to produce a summary. This paper presents a comprehensive comparison between several summarisation methods based on term specificity estimation in order to find out which one performs better. In the(More)
With the appearance of Semantic Web technologies, it becomes possible to develop novel, sophisticated question answering systems, where ontologies are usually used as the core knowledge component. In the EU-funded project, QALL-ME, a domain-specific ontology was developed and applied for question answering in the domain of tourism, along with the assistance(More)
* The paper comparatively studies methods of feature weighting in application to the task of cooccurrence-based classification of words according to their meaning. We explore parameter optimization of several weighting methods frequently used for similar problems such as text classification. We find that successful application of all the methods crucially(More)
Papers discussing anaphora resolution algorithms or systems usually focus on the intrinsic evaluation of the algorithm/system and not on the issue of extrinsic evaluation. In the context of anaphora resolution , extrinsic evaluation concerns the impact of an anaphora resolution module on a larger NLP system of which it is part. In this paper we explore the(More)