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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Semantic Relatedness and Taxonomic Word Embeddings ... Kacmajor, Magdalena; Kelleher, John D.; Klubicka, Filip. - : arXiv, 2020 BASE Show details 2 English WordNet Taxonomic Random Walk Pseudo-Corpora Klubicka, Filip; Maldonado, Alfredo; Mahalunkar, Abhijit... In: Conference papers (2020) BASE Show details 3 Language related issues for machine translation between closely related south Slavic languages Arcan, Mihael; Klubicka, Filip; Popovic, Maja. - : The COLING 2016 Organizing Committee, 2019 BASE Show details 4 Synthetic, Yet Natural: Properties of WordNet Random Walk Corpora and the impact of rare words on embedding performance Klubicka, Filip; Mahalunkar, Abhijit; Maldonado, Alfredo... In: Conference papers (2019) BASE Show details 5 Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings Maldonado, Alfredo; Klubicka, Filip; Kelleher, John D. In: Articles (2019) BASE Show details 6 Quantitative Fine-grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian Sanchez-Cartagena, Victor Manuel; Toral, Antonio; Klubicka, Filip In: Articles (2018) BASE Show details 7 Is it worth it? Budget-related evaluation metrics for model selection Klubicka, Filip; Salton, Giancarlo; Kelleher, John D. In: Conference papers (2018) BASE Show details 8 hr500k – A Reference Training Corpus of Croatian. Erjavec, Tomaž; Ljubešić, Nikola; Klubicka, Filip; Agić, Željko; Batanović, Vuk In: Conference papers (2018) Abstract: In this paper we present hr500k, a Croatian reference training corpus of 500 thousand tokens, segmented at document, sentence and word level, and annotated for morphosyntax, lemmas, dependency syntax, named entities, and semantic roles. We present each annotation layer via basic label statistics and describe the final encoding of the resource in CoNLL and TEI formats. We also give a description of the rather turbulent history of the resource and give insights into the topic and genre distribution in the corpus. Finally, we discuss further enrichments of the corpus with additional layers, which are already underway. Keyword: annotation; computational linguistics; Croatian; Digital Humanities; linguistic resource; machine learning; reference corpus; Slavic Languages and Societies URL: https://arrow.tudublin.ie/cgi/viewcontent.cgi?article=1254&context=scschcomcon https://arrow.tudublin.ie/scschcomcon/244 BASE Hide details

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