Word Sense Disambiguation with Automatically Acquired Knowledge
نویسندگان
چکیده
منابع مشابه
Word Sense Disambiguation Using Automatically Acquired Verbal Preferences
The selectional preferences of verbal predicates are an important component of a computational lexicon. They have frequently been cited as being useful for wsd, alongside other sources of knowledge. We evaluate automatically acquired selectional preferences on the level playing eld provided by senseval to examine to what extent they help in WSD.
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In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. The first (or predominant) sense heuristic assumes the availability of handtagged data. Whilst there are hand-tagged corpora available for some languages, these are relatively small in size and many word forms either do not o...
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We present a novel almost-unsupervised approach to the task of Word Sense Disambiguation (WSD). We build sense examples automatically, using large quantities of Chinese text, and English-Chinese and Chinese-English bilingual dictionaries, taking advantage of the observation that mappings between words and meanings are often different in typologically distant languages. We train a classifier on ...
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We present a corpus based approach to word sense disambiguation that only requires information that can be automatically extracted from untagged text We use unsupervised techniques to estimate the pa rameters of a model describing the conditional distri bution of the sense group given the known contextual features Both the EM algorithm and Gibbs Sampling are evaluated to determine which is most...
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We present an unsupervised approach to Word Sense Disambiguation (WSD). We automatically acquire English sense examples using an English-Chinese bilingual dictionary, Chinese monolingual corpora and Chinese-English machine translation software. We then train machine learning classifiers on these sense examples and test them on two gold standard English WSD datasets, one for binary and the other...
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ژورنال
عنوان ژورنال: IEEE Intelligent Systems
سال: 2012
ISSN: 1541-1672
DOI: 10.1109/mis.2010.134