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Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection

Tahmasebi, Nina; Hengchen, Simon; Schlechtweg, Dominik; McGillivray, Barbara; Dubossarsky, Haim


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    <dct:title>Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection</dct:title>
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    <dcat:keyword>unsupervised lexical semantic change detection, semantic change, SemEval2020, Kubhist2</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2020-02-19</dct:issued>
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    <dct:description>&lt;p&gt;This data collection contains the Swedish test data for &lt;a href="https://languagechange.org/semeval"&gt;SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection:&lt;/a&gt;&lt;/p&gt; &lt;p&gt;- a Swedish text corpus pair (`corpus1/`, `corpus2/`)&lt;br&gt; - 31 lemmas which have been annotated for their lexical semantic change between the two corpora (`targets.txt`)&lt;/p&gt; &lt;p&gt;We sample from the KubHist2 corpus, digitized by the National Library of Sweden, and available through the Spr&amp;aring;kbanken corpus infrastructure Korp (&lt;a href="https://www.researchgate.net/profile/Markus_Forsberg/publication/266352576_Korp_-_the_corpus_infrastructure_of_Sprakbanken/links/55bf1ee008aed621de121ba3/Korp-the-corpus-infrastructure-of-Sprakbanken.pdf"&gt;Borin et al., 2012&lt;/a&gt;). The full corpus is available through a CC BY (attribution) license. Each word for which the lemmatizer in the Korp pipelien has found a lemma is replaced with the lemma. In cases where the lemmatizer cannot find a lemma, we leave the word as is (i.e., unlemmatized, no lower-casing). KubHist contains very frequent OCR errors, especially for the older data.More detail about the properties and quality of the Kubhist corpus can be found in (&lt;a href="https://www.diva-portal.org/smash/get/diva2:1358014/FULLTEXT01.pdf#page=28"&gt;Adesam et al., 2019&lt;/a&gt;).&lt;/p&gt; &lt;p&gt;Lars Borin, Markus Forsberg, and Johan Roxendal. &amp;quot;Korp-the corpus infrastructure of Spr&amp;aring;kbanken.&amp;quot; &lt;em&gt;LREC&lt;/em&gt;. 2012.&lt;/p&gt; &lt;p&gt;Adesam, Yvonne, Dana Dann&amp;eacute;lls, and Nina Tahmasebi. &amp;quot;Exploring the Quality of the Digital Historical Newspaper Archive KubHist.&amp;quot; &lt;em&gt;DHN&lt;/em&gt;. 2019.&lt;/p&gt; &lt;p&gt;Corpus 1&lt;/p&gt; &lt;p&gt;- based on: &lt;a href="https://spraakbanken.gu.se/korp/?mode=kubhist"&gt;Kubhist2&lt;/a&gt;&lt;br&gt; - language: Swedish&lt;br&gt; - time covered: 1790-1830&lt;br&gt; - size: ~71 million tokens&lt;br&gt; - format: lemmatized, sentence length &amp;gt; 9 (before removal of punctuation), no punctuation, sentences randomly shuffled&lt;br&gt; - encoding: UTF-8&lt;br&gt; - note: contains frequent OCR errors&lt;/p&gt; &lt;p&gt;Corpus 2&lt;/p&gt; &lt;p&gt;- based on:&amp;nbsp;&lt;a href="https://spraakbanken.gu.se/korp/?mode=kubhist"&gt;Kubhist2&lt;/a&gt;&lt;br&gt; - language: Swedish&lt;br&gt; - time covered: 1895-1903&lt;br&gt; - size: ~111 million tokens&lt;br&gt; - format: lemmatized, sentence length &amp;gt; 9 (before removal of punctuation), no punctuation, sentences randomly shuffled&lt;br&gt; - encoding: UTF-8&lt;br&gt; - note: contains OCR errors&lt;/p&gt; &lt;p&gt;Find more information on the data and SemEval2020 Task 1 in the paper referenced below.&lt;/p&gt; &lt;p&gt;Reference:&lt;/p&gt; &lt;p&gt;Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky and Nina Tahmasebi.&lt;a href="https://competitions.codalab.org/competitions/20948"&gt;SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection&lt;/a&gt;. To appear in SemEval@COLING2020.&lt;/p&gt;</dct:description>
    <dct:description>The creation of the data was supported by the project Towards Computational Lexical Semantic Change Detection funded by a project grant from the Swedish Research Council (2019–2022; dnr 2018-01184). It has also been created as part of the effort to construct and develop a Swedish national research infrastructure in support of research based on language data. This infrastructure -- Nationella språkbanken (the Swedish National Language Bank) -- is jointly funded for the period 2018--2024 by the Swedish Research Council (grant number 2017-00626) and its 10 partner institutions.</dct:description>
    <dct:description>{"references": ["Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky and Nina Tahmasebi.SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection. To appear in SemEval@COLING2020."]}</dct:description>
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