Multi-Word Expressions (MWEs) are prevalent in text and are also, on average, less polysemous than mono-words. This suggests that accurate MWE detection should lead to a nontrivial improvement in Word Sense Disambiguation (WSD). We show that a straightforward MWE detection strategy, due to Arranz et al. (2005), can increase a WSD algorithm’s baseline f-measure by 5 percentage points. Our measur...

A major obstacle to part-of-speech (=POS) tagging of Northern Sotho (Bantu, S 32) are ambiguous function words. Many are highly polysemous and very frequent in texts, and their local context is not always distinctive. With certain taggers, this issue leads to comparatively poor results (between 88 and 92 % accuracy), especially when sizeable tagsets (over 100 tags) are used. We use the RF-tagge...

Abstract This paper discusses methodological issues related to the implementation of experimental studies that investigate processing literal and metaphorical expressions. The first central aim is discuss questions arising from current research on figurative language, such as use heterogeneous stimuli their suitability for investigating language. At center discussion contextual cognitive domina...

Different types of word knowledge require different approaches to teaching. It is argued that learning senses words takes place through constantly encountering in contexts. Experimental studies also show comprehension unknown (Iravani and Ghasemi, 2013) ambiguity resolution polysemous (Watanabe, 2014) are facilitated when the context available. Verbal polysemy especially closely related context...

This study explores the role of corpus linguistics in addressing lexicographic challenges over past ten years. It examines 25 studies published from 2012 to 2021 that employed solutions solve problems. Challenging tasks are either relevant macrostructure or microstructure dictionaries. In decade, lexicographers made extensive use tools create dictionaries and improve existing ones. effort inclu...

Regular polysemy was extensively investigated in lexical semantics, but this phenomenon has been very little studied in distributional semantics. We propose a model for regular polysemy detection that is based on sense vectors and allows to work directly with senses in semantic vector space. Our method is able to detect polysemous words that have the same regular sense alternation as in a given...

Automatically generated databases of English paraphrases have the drawback that they return a single list of paraphrases for an input word or phrase. This means that all senses of polysemous words are grouped together, unlike WordNet which partitions different senses into separate synsets. We present a new method for clustering paraphrases by word sense, and apply it to the Paraphrase Database ...

Chinese sentences are written as sequences of characters, which are elementary units of syntax and semantics. Characters are highly polysemous in forming words. We present a position-sensitive skip-gram model to learn multi-prototype Chinese character embeddings, and explore the usefulness of such character embeddings to Chinese NLP tasks. Evaluation on character similarity shows that multi-pro...

We propose a multilingual unsupervised Word Sense Disambiguation (WSD) task for a sample of English nouns. Instead of providing manually sense-tagged examples for each sense of a polysemous noun, our sense inventory is built up on the basis of the Europarl parallel corpus. The multilingual setup involves the translations of a given English polysemous noun in five supported languages, viz. Dutch...

In many languages, the same words are used to express epistemic and root modality. These modals further tend to interact with tense and aspect in systematic ways, based on their interpretation. Is this pattern accidental, or a consequence of grammar or meaning? I address this question by: (i) comparing ‘grammatical’ modals to verbs/adjectives that share meanings with modals, but not the same sc...