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SemEval2020 Task 1

Citation Information

Språkbanken Text (2024). SemEval2020 Task 1 (updated: 2024-01-25). [Data set]. Språkbanken Text. https://doi.org/10.23695/d79w-qa67
BibTeX Additional ways to cite the dataset.
Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection (extracts from Kubhist v2)

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This data collection contains the Swedish test data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection:

- a Swedish text corpus pair (`corpus1/`, `corpus2/`)
- 31 lemmas which have been annotated for their lexical semantic change between the two corpora (`targets.txt`)

We sample from the KubHist2 corpus, digitized by the National Library of Sweden, and available through the Språkbanken corpus infrastructure Korp (Borin et al., 2012). The full corpus is available through a CC BY (attribution) license.

Each word for which the lemmatizer in the Korp pipeline 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 (Adesam et al., 2019).

Lars Borin, Markus Forsberg, and Johan Roxendal. Korp-the corpus infrastructure of Språkbanken. LREC. 2012.

* Yvonne Adesam, Dana Dannélls, and Nina Tahmasebi. Exploring the Quality of the Digital Historical Newspaper Archive KubHist. DHN. 2019.

__Corpus 1__

- based on: Kubhist2
- language: Swedish
- time covered: 1790-1830
- size: ~71 million tokens
- format: lemmatized, sentence length >= 9 (before removal of punctuation), no punctuation, sentences randomly shuffled
- encoding: UTF-8
- note: contains frequent OCR errors

__Corpus 2__

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p> - based on: Kubhist2
- language: Swedish
- time covered: 1895-1903
- size: ~111 million tokens
- format: lemmatized, sentence length >= 9 (before removal of punctuation), no punctuation, sentences randomly shuffled
- encoding: UTF-8
- note: contains OCR errors

Reference this testset as:
Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky and Nina Tahmasebi.
SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection:.In Proceedings of the 14th International Workshop on Semantic Evaluation, Barcelona, Spain, 2020. Association for Computational Linguistics.

More information can be found on Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection and SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection.

File Size Modified Licence
semeval2020_ulscd_swe.zip
semeval2020_ulscd_swe.zip (zip)
956.05 MB 2024-01-25 CC BY 4.0
attribution

Type

  • Corpus
  • Training and evaluation data

Language

Swedish

Size

Tokens: 182,000,000

Updated

2024-01-25

Contact

Språkbanken
sb-info@svenska.gu.se