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      Cross-Lingual Induction and Transfer of Verb Classes Based on Word Vector Space Specialisation

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          Abstract

          Existing approaches to automatic VerbNet-style verb classification are heavily dependent on feature engineering and therefore limited to languages with mature NLP pipelines. In this work, we propose a novel cross-lingual transfer method for inducing VerbNets for multiple languages. To the best of our knowledge, this is the first study which demonstrates how the architectures for learning word embeddings can be applied to this challenging syntactic-semantic task. Our method uses cross-lingual translation pairs to tie each of the six target languages into a bilingual vector space with English, jointly specialising the representations to encode the relational information from English VerbNet. A standard clustering algorithm is then run on top of the VerbNet-specialised representations, using vector dimensions as features for learning verb classes. Our results show that the proposed cross-lingual transfer approach sets new state-of-the-art verb classification performance across all six target languages explored in this work.

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          • Record: found
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          SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation

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            • Article: not found

            The Proposition Bank: An Annotated Corpus of Semantic Roles

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              • Record: found
              • Abstract: not found
              • Article: not found

              BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network

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                Author and article information

                Journal
                21 July 2017
                Article
                1707.06945
                99fbcc79-989d-4dcc-a50d-5122262ef5ef

                http://creativecommons.org/licenses/by/4.0/

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                Custom metadata
                EMNLP 2017 (long paper)
                cs.CL

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