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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 – 7 of 7 1 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ... Ponti, Edoardo; Glavaš, Goran; Majewska, Olga. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 2 Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ... Vulic, Ivan; Baker, Simon; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 3 Spatial multi-arrangement for clustering and multi-way similarity dataset construction ... Majewska, Olga; McCarthy, D; Van Den Bosch, J. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 4 Spatial multi-arrangement for clustering and multi-way similarity dataset construction Majewska, Olga; McCarthy, D; van den Bosch, J. - : European Language Resources Association, 2020. : LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings, 2020 BASE Show details 5 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning Liu, Qianchu; Korhonen, Anna-Leena; Majewska, Olga. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 BASE Show details 6 Investigating the cross-lingual translatability of VerbNet-style classification. ... Majewska, Olga; Vulić, Ivan; McCarthy, Diana; Huang, Yan; Murakami, Akira; Laippala, Veronika; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2018 Abstract: VerbNet-the most extensive online verb lexicon currently available for English-has proved useful in supporting a variety of NLP tasks. However, its exploitation in multilingual NLP has been limited by the fact that such classifications are available for few languages only. Since manual development of VerbNet is a major undertaking, researchers have recently translated VerbNet classes from English to other languages. However, no systematic investigation has been conducted into the applicability and accuracy of such a translation approach across different, typologically diverse languages. Our study is aimed at filling this gap. We develop a systematic method for translation of VerbNet classes from English to other languages which we first apply to Polish and subsequently to Croatian, Mandarin, Japanese, Italian, and Finnish. Our results on Polish demonstrate high translatability with all the classes (96% of English member verbs successfully translated into Polish) and strong inter-annotator agreement, ... URL: https://dx.doi.org/10.17863/cam.23410 https://www.repository.cam.ac.uk/handle/1810/276130 BASE Hide details 7 Investigating the cross-lingual translatability of VerbNet-style classification. Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Springer Science and Business Media LLC, 2018. : Lang Resour Eval, 2018 BASE Show details

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