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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 Page: 1 2 Hits 1 – 20 of 21 1 Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification Nedumpozhimana, Vasudevan; Klubička, Filip; Kelleher, John D. In: Front Artif Intell (2022) BASE Show details 2 Training corpus hr500k 1.0 Ljubešić, Nikola; Agić, Željko; Klubička, Filip. - : Jožef Stefan Institute, 2018 BASE Show details 3 Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian ... Klubička, Filip; Toral, Antonio; Sánchez-Cartagena, Víctor M.. - : arXiv, 2018 BASE Show details 4 Is it worth it? Budget-related evaluation metrics for model selection ... Klubička, Filip; Salton, Giancarlo D.; Kelleher, John D.. - : arXiv, 2018 Abstract: Creating a linguistic resource is often done by using a machine learning model that filters the content that goes through to a human annotator, before going into the final resource. However, budgets are often limited, and the amount of available data exceeds the amount of affordable annotation. In order to optimize the benefit from the invested human work, we argue that deciding on which model one should employ depends not only on generalized evaluation metrics such as F-score, but also on the gain metric. Because the model with the highest F-score may not necessarily have the best sequencing of predicted classes, this may lead to wasting funds on annotating false positives, yielding zero improvement of the linguistic resource. We exemplify our point with a case study, using real data from a task of building a verb-noun idiom dictionary. We show that, given the choice of three systems with varying F-scores, the system with the highest F-score does not yield the highest profits. In other words, in our case ... : 7 pages, 1 figure, 5 tables, In proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1807.06998 https://dx.doi.org/10.48550/arxiv.1807.06998 BASE Hide details 5 Croatian Twitter training corpus ReLDI-NormTag-hr 1.1 Ljubešić, Nikola; Farkaš, Daša; Klubička, Filip. - : Jožef Stefan Institute, 2017 BASE Show details 6 Serbian Twitter training corpus ReLDI-NormTag-sr 1.0 Ljubešić, Nikola; Farkaš, Daša; Klubička, Filip. - : Jožef Stefan Institute, 2017 BASE Show details 7 Croatian Twitter training corpus ReLDI-NormTag-hr 1.0 Ljubešić, Nikola; Farkaš, Daša; Klubička, Filip. - : Jožef Stefan Institute, 2017 BASE Show details 8 Serbian Twitter training corpus ReLDI-NormTag-sr 1.1 Ljubešić, Nikola; Farkaš, Daša; Klubička, Filip. - : Jožef Stefan Institute, 2017 BASE Show details 9 Fine-grained human evaluation of neural versus phrase-based machine translation ... Klubička, Filip; Toral, Antonio; Sánchez-Cartagena, Víctor M.. - : arXiv, 2017 BASE Show details 10 Serbian-English parallel corpus srenWaC 1.0 Ljubešić, Nikola; Esplà-Gomis, Miquel; Ortiz Rojas, Sergio. - : Jožef Stefan Institute, 2016 BASE Show details 11 Finnish-English parallel corpus fienWaC 1.0 Ljubešić, Nikola; Esplà-Gomis, Miquel; Ortiz Rojas, Sergio. - : Jožef Stefan Institute, 2016 BASE Show details 12 Serbian web corpus srWaC 1.1 Ljubešić, Nikola; Klubička, Filip. - : Jožef Stefan Institute, 2016 BASE Show details 13 Inflectional lexicon hrLex 1.0 Ljubešić, Nikola; Klubička, Filip. - : Faculty of Humanities and Social Sciences, University of Zagreb, 2016 BASE Show details 14 Inflectional lexicon hrLex 1.2 Ljubešić, Nikola; Klubička, Filip; Boras, Damir. - : Faculty of Humanities and Social Sciences, University of Zagreb, 2016 BASE Show details 15 Tourism English-Croatian Parallel Corpus 2.0 Toral, Antonio; Esplà-Gomis, Miquel; Klubička, Filip. - : Abu-MaTran project, 2016 BASE Show details 16 Inflectional lexicon srLex 1.2 Ljubešić, Nikola; Klubička, Filip; Boras, Damir. - : Faculty of Humanities and Social Sciences, University of Zagreb, 2016 BASE Show details 17 Croatian-English parallel corpus hrenWaC 2.0 Ljubešić, Nikola; Esplà-Gomis, Miquel; Ortiz Rojas, Sergio. - : Jožef Stefan Institute, 2016 BASE Show details 18 Inflectional lexicon srLex 1.0 Ljubešić, Nikola; Klubička, Filip. - : Faculty of Humanities and Social Sciences, University of Zagreb, 2016 BASE Show details 19 Croatian web corpus hrWaC 2.1 Ljubešić, Nikola; Klubička, Filip. - : Jožef Stefan Institute, 2016 BASE Show details 20 Slovene-English parallel corpus slenWaC 1.0 Ljubešić, Nikola; Esplà-Gomis, Miquel; Ortiz Rojas, Sergio. - : Jožef Stefan Institute, 2016 BASE Show details Page: 1 2

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