Feature selection in Word Sense Disambiguation (WSD) is as important as the selection of algorithm to remove sense ambiguity. Bag-of-word (BoW) features comprise the information of neighbors around the ambiguous target word without considering any relation between words. In this study, we investigate the effect of BoW features and Bag-of-bigrams (BoB) on Turkish WSD and compare the results with...

This paper compares several methods (MI, T-score, Dice) for the extraction of collocations and presents a new method called Gravity Counts. The respective methods are evaluated and compared, measuring the combinability and collocability for each pair of words within the moving span of three words in the corpus of “The Times” newspaper for the year 1995. The collocability of words is the basis f...

In this paper, we describe TANGO as a collocational concordancer for looking up collocations. The system was designed to answer user’s query of bilingual collocational usage for nouns, verbs and adjectives. We first obtained collocations from the large monolingual British National Corpus (BNC). Subsequently, we identified collocation instances and translation counterparts in the bilingual corpu...

This study aims at determining whether collocational features automatically extracted from EFL (English as a foreign language) texts are useful for quality scoring, and allow the improvement of a competitive baseline based on, amongst other factors, bigram frequencies. The collocational features were gathered by assigning to each bigram in an EFL text eight association scores computed on the ba...

Properties can be mapped to features in a machine learning algorithm in different ways, potentially yielding different results. In previous work, we experimented with various approaches to organizing collocational properties into features in a probabilistic classifier. It was found that one type of organization in particular, which is rarely used in NLP, allows one to take advantage of infreque...

We present Collocation Assistant, a prototype of a collocational aid designed to promote the collocational competence of learners of Japanese as a second language (JSL). Focusing on noun-verb constructions, the tool automatically flags possible collocation errors and suggests better collocations by using corrections extracted from a large annotated Japanese language learner corpus. Each suggest...