dc.contributor.author | Barančíková, Petra |
dc.contributor.author | Bojar, Ondřej |
dc.date.accessioned | 2019-12-05T09:18:04Z |
dc.date.available | 2019-12-05T09:18:04Z |
dc.date.issued | 2019-12-03 |
dc.identifier.uri | http://hdl.handle.net/11234/1-3123 |
dc.description | COSTRA 1.0 is a dataset of Czech complex sentence transformations. The dataset is intended for the study of sentence-level embeddings beyond simple word alternations or standard paraphrasing. The dataset consist of 4,262 unique sentences with average length of 10 words, illustrating 15 types of modifications such as simplification, generalization, or formal and informal language variation. The hope is that with this dataset, we should be able to test semantic properties of sentence embeddings and perhaps even to find some topologically interesting “skeleton” in the sentence embedding space. |
dc.language.iso | ces |
dc.publisher | Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL) |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/825303 |
dc.rights | Creative Commons - Attribution 4.0 International (CC BY 4.0) |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ |
dc.subject | sentences |
dc.subject | sentence embeddings |
dc.subject | paraphrases |
dc.subject | semantic relations |
dc.title | COSTRA 1.0: A Dataset of Complex Sentence Transformations |
dc.type | corpus |
metashare.ResourceInfo#ContentInfo.mediaType | text |
dc.rights.label | PUB |
has.files | yes |
branding | LINDAT / CLARIAH-CZ |
contact.person | Petra Barančíková barancikova@ufal.mff.cuni.cz Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL) |
sponsor | Czech Science Foundation 19-26934X Neural Representations in Multi-modal and Multi-lingual Modelling nationalFunds |
sponsor | European Union EC/H2020/825303 Bergamot - Browser-based Multilingual Translation euFunds info:eu-repo/grantAgreement/EC/H2020/825303 |
size.info | 5544 sentences |
files.size | 119547 |
files.count | 1 |
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