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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 3 4 Hits 1 – 20 of 71 1 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 2 BioVerbNet: a large semantic-syntactic classification of verbs in biomedicine. ... Majewska, Olga; Collins, Charlotte; Baker, Simon. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 3 BioVerbNet: a large semantic-syntactic classification of verbs in biomedicine. Majewska, Olga; Collins, Charlotte; Baker, Simon; Björne, Jari; Brown, Susan Windisch; Korhonen, Anna-Leena; Palmer, Martha. - : Springer Science and Business Media LLC, 2021. : J Biomed Semantics, 2021 Abstract: BACKGROUND: Recent advances in representation learning have enabled large strides in natural language understanding; However, verbal reasoning remains a challenge for state-of-the-art systems. External sources of structured, expert-curated verb-related knowledge have been shown to boost model performance in different Natural Language Processing (NLP) tasks where accurate handling of verb meaning and behaviour is critical. The costliness and time required for manual lexicon construction has been a major obstacle to porting the benefits of such resources to NLP in specialised domains, such as biomedicine. To address this issue, we combine a neural classification method with expert annotation to create BioVerbNet. This new resource comprises 693 verbs assigned to 22 top-level and 117 fine-grained semantic-syntactic verb classes. We make this resource available complete with semantic roles and VerbNet-style syntactic frames. RESULTS: We demonstrate the utility of the new resource in boosting model performance in document- and sentence-level classification in biomedicine. We apply an established retrofitting method to harness the verb class membership knowledge from BioVerbNet and transform a pretrained word embedding space by pulling together verbs belonging to the same semantic-syntactic class. The BioVerbNet knowledge-aware embeddings surpass the non-specialised baseline by a significant margin on both tasks. CONCLUSION: This work introduces the first large, annotated semantic-syntactic classification of biomedical verbs, providing a detailed account of the annotation process, the key differences in verb behaviour between the general and biomedical domain, and the design choices made to accurately capture the meaning and properties of verbs used in biomedical texts. The demonstrated benefits of leveraging BioVerbNet in text classification suggest the resource could help systems better tackle challenging NLP tasks in biomedicine. URL: https://doi.org/10.17863/CAM.72650 https://www.repository.cam.ac.uk/handle/1810/325196 BASE Hide details 4 Towards zero-shot language modeling ... Ponti, Edoardo; Vulić, I; Cotterell, R. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 5 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ... Ponti, Edoardo; Glavaš, Goran; Majewska, Olga. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 6 Cross-lingual semantic specialization via lexical relation induction ... Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 7 Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization ... Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 8 SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ... Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 9 Do we really need fully unsupervised cross-lingual embeddings? ... Vulić, I; Glavaš, G; Reichart, R. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 10 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 11 Probing Pretrained Language Models for Lexical Semantics ... Vulic, Ivan; Ponti, Edoardo; Litschko, Robert. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 12 On the relation between linguistic typology and (limitations of) multilingual language modeling ... Gerz, Daniela; Vulić, I; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 13 The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures ... Dubossarsky, Haim; Vulic, Ivan; Reichart, Roi. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 14 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 15 Cross-lingual semantic specialization via lexical relation induction Ponti, Edoardo; Vulić, I; Glavaš, G. - : EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2020 BASE Show details 16 On the relation between linguistic typology and (limitations of) multilingual language modeling Gerz, Daniela; Vulić, I; Ponti, Edoardo. - : Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, 2020 BASE Show details 17 Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization Ponti, Edoardo; Vulić, I; Glavaš, G. - : Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, 2020 BASE Show details 18 The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures Dubossarsky, Haim; Vulic, Ivan; Reichart, Roi. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 BASE Show details 19 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 20 Probing Pretrained Language Models for Lexical Semantics Vulic, Ivan; Ponti, Edoardo; Litschko, Robert. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 BASE Show details Page: 1 2 3 4

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