Papers by Denis Teslenko
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages (L18-1)
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Dmitry Ustalov, Denis Teslenko, Alexander Panchenko, Mikhail Chernoskutov, Chris Biemann, Simone Paolo Ponzetto
| Challenge: | Existing systems for word sense disambiguation are limited to the Russian language and lack of resources to address the problem. |
| Approach: | They propose an unsupervised system for word sense disambiguation that uses a traditional vector space model to estimate the most similar word sense corresponding to its context. |
| Outcome: | The proposed system outperforms the sparse mode on all datasets according to the adjusted Rand index. |
Word Sense Disambiguation for 158 Languages using Word Embeddings Only (2020.lrec-1)
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Varvara Logacheva, Denis Teslenko, Artem Shelmanov, Steffen Remus, Dmitry Ustalov, Andrey Kutuzov, Ekaterina Artemova, Chris Biemann, Simone Paolo Ponzetto, Alexander Panchenko
| Challenge: | Existing methods of disambiguation of word senses are based on knowledge bases, taxonomies, and other externally built resources. |
| Approach: | They propose a method that takes a pre-trained word embedding model and induces a fully-fledged word sense inventory for 158 languages. |
| Outcome: | The proposed model is based on a pre-trained word embedding model and induces a fully-fledged word sense inventory in 158 languages. |