Hyponymy relation acquisition has been extensively studied. However, the informativeness of acquired hypernyms has not been sufficiently discussed. We found that the hypernyms in automatically acquired hyponymy relations are often too vague for their hyponyms. For instance, “work” is a vague hypernym for “work→Seven Samurai” and “work→1Q84”. These vague hypernyms sometimes cause the lower accuracy for NLP applications such as information retrieval or question answering. In this paper, we propose a method of making (vague) hypernyms more specific exploting Wikipedia. For instance, our method generates two intermediate nodes “work by Akira Kurosawa” and “work by film director” for a original hyponymy relation “work→Seven Samurai”. We show that our method acquires 2,719,441 hyponymy relations with the first intermediate concepts (such as “work by Akira Kurosawa”) with 85.3% weighted precision and 6,347,472 hyponymy relations with the second intermediate concepts (such as “work by film director”) with 78.6% weighted precision. Furthermore, we confirm that hyponymy relaitons acquired by our method can be interpreted as “object–attribute–value”.

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It is said that Vietnamese is a language with highly ambiguous words. However, there has been no published Word Sense Disambiguation (WSD hereafter) research on this language. This current research is the first attempt to study Vietnamese WSD. Especially, we would like to explore the effective features for training WSD classifiers and verify the applicability of the ‘pseudoword’ technique to both investigating effectiveness of features and training WSD classifiers. Three tasks have been conducted, using two corpora which were built manually based on Vietnamese Treebank and automatically by applying pseudowords technique. Experiment results showed that Bag-Of-Word feature performs well for all three categories of words (verbs, nouns, and adjectives). However, its combination with POS, Collocation or Syntactic features can not significantly improve the performance of WSD classifiers. Moreover, the experiment results confirmed that pseudoword is a suitable technique to explore the effectiveness of features in disambiguation of Vietnamese verbs and adjectives. Furthermore, we empirically evaluated the applicability of the pseudoword technique as an unsupervised learning method for real Vietnamese WSD.

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