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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 – 4 of 4 1 Acquiring verb classes through bottom-up semantic verb clustering ... Majewska, Olga; McCarthy, D; Vulić, I. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 2 Investigating the cross-lingual translatability of VerbNet-style classification. ... Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 3 Investigating the cross-lingual translatability of VerbNet-style classification. Majewska, Olga; Vulić, Ivan; McCarthy, Diana; Huang, Yan; Murakami, Akira; Laippala, Veronika; Korhonen, Anna-Leena. - : Springer Science and Business Media LLC, 2018. : Lang Resour Eval, 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, revealing a promising degree of overlap in the resultant classifications. The results on other languages are equally promising. This demonstrates that VerbNet classes have strong cross-lingual potential and the proposed method could be applied to obtain gold standards for automatic verb classification in different languages. We make our annotation guidelines and the six language-specific verb classifications available with this paper. URL: https://www.repository.cam.ac.uk/handle/1810/276130 https://doi.org/10.17863/CAM.23410 BASE Hide details 4 Acquiring verb classes through bottom-up semantic verb clustering Majewska, Olga; McCarthy, D; Vulić, I. - : LREC 2018 - 11th International Conference on Language Resources and Evaluation, 2018 BASE Show details

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