Word Sense
I2R: Three Systems for Word Sense Discrimination, Chinese Word Sense Disambiguation, and English Word Sense Disambiguation
... (word sense discrimination), task 5 (Chinese word sense disambiguation), and the first subtask in task 17 (English word sense ...target word in untagged data, and then ...
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Grounded Word Sense Translation
... grounded word sense translation, ...source word given the corresponding textual and vi- sual ...improve word-level (lexical) translation ...
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Sense Embeddings in Knowledge Based Word Sense Disambiguation
... creating sense vectors for any dictionary, by using an existing word embeddings model, and summing the vectors of the terms inside a sense’s definition, weighted in function of their part of speech and ...
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Measuring the Impact of Sense Similarity on Word Sense Induction
... for Word Sense Dis- ambiguation (Chugur et ...learn sense dis- tinctions, measuring the impact of sense related- ness on the harder problem of WSI remains unad- ...limit sense ambiguity ...
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Bayesian Word Sense Induction
... grained sense distinctions. Cai et al. (2007) pro- pose to use LDA’s word-topic distributions as fea- tures for training a supervised WSD ...target word, a topic is sampled from the docu- ment’s ...
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Subjectivity Word Sense Disambiguation
... (Hovy et al., 2006)). We also have evidence that a moderate amount of manual annotation would be worth the effort. For example, let us order the lexi- con entries from highest to lowest by frequency in the MPQA corpus. ...
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Graded Word Sense Assignment
... of word sense applicability, using a recent dataset with graded annotation (Erk et ...of word mean- ing compared to a system that focuses on mak- ing clear cut ...graded sense as- signment ...
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Gamification for Word Sense Labeling
... All disambiguation models rely on gold standard data from human annotators, but this data is time- consuming and expensive to obtain. In the context of constructing the Groningen Meaning Bank (GMB, Basile et al., 2012), ...
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Word Relatives in Context for Word Sense Disambiguation
... The current situation for Word Sense Dis- ambiguation (WSD) is somewhat stuck due to lack of training data. We present in this paper a novel disambiguation al- gorithm that improves previous systems based ...
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Crowdsourcing Word Sense Definition
... for word sense disambiguation (Snow et ...modify sense inventories. But the origi- nal sense inventory construction has always been left to the ...
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An Evaluation of Graded Sense Disambiguation using Word Sense Induction
... Graded word sense annotation conveys multiple lev- els of information, both in which senses are present and their relative levels of applicability; and so, no single evaluation measure alone is appropriate ...
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Multi sense Embeddings through a Word Sense Disambiguation Process
... analysis, word embeddings, machine learning, artificial neural networks (NN) and ...2014), word embeddings techniques have received much attention in the NLP commu- ...2013), word sense ...
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Detecting Multi Word Expressions Improves Word Sense Disambiguation
... Multi-Word Expressions (MWEs) are preva- lent in text and are also, on average, less poly- semous than mono-words. This suggests that accurate MWE detection should lead to a non- trivial improvement in Word ...
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Sense Embedding Learning for Word Sense Induction
... Conventional word sense induction (WSI) methods usually represent each instance with discrete linguistic features or co- occurrence features, and train a model for each polysemous word ...learn ...
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Making Sense of Word Sense Variation
... the word sense assigned by annotators, the annota- tors, and the instances ...Annotator Sense. We denote the six annotators as A1 through A6, and word senses by WordNet sense ...same ...
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Making Sense of Word Embeddings
... learning word sense ...learn sense representations from corpora or rely on sense invento- ries from lexical resources, our approach can induce a sense inventory from ex- isting ...
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Word Sense Disambiguation using a dictionary for sense similarity measure
... on word sense disambiguation on definitions of the dictionary itself (section 5), but the method is expected to be more general, although this has not been tested ...
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Clustering Paraphrases by Word Sense
... input word like bug. It is generally recognized that optimal sense granu- larity depends on the application (Palmer et ...most word sense disambiguation systems achieve better performance when ...
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Word Sense Disambiguation using Static and Dynamic Sense Vectors
... static sense vector in word space, which is the centroid of the context ...another sense vectors for each sense of the target ...dynamic sense vectors because they are changed according ...
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Use of Sense Marking for Improving WordNet Coverage
... each word of the corpus accurately with the WordNet sense or lexi- ...be sense tagged precisely by humans using a stan- dard lexicon. A word may have multiple senses and to identify which ...
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