# Datasets in LSCDBenchmark
The following table shows all the data set we integrated into benchmark.
| Data set | LGS | n | N/V/A | |U| | AN | JUD | Task | t1 | t2 | Reference | Version |
|:-------------:|:---:|:---:|:--------:|:-------------:|:--:|:---:|:----------------------:|:-------------:|:-------------:|:---------:|:--------:|
| DWUG | DE | 48 | 32/14/2 | 178 | 8 | 37k | WiC, WSI, LSCD (B,G,C) | 1800–1899 | 1946–1990 | [Schlechtweg et al. (2021)](#paper1) | 2.2.0 |
| DWUG | EN | 40 | 36/4/0 | 189 | 9 | 29k | WiC, WSI, LSCD (B,G,C) | 1810–1860 | 1960–2010 | [Schlechtweg et al. (2021)](#paper1) | 2.0.1 |
| DWUG | SV | 40 | 31/6/3 | 168 | 5 | 20k | WiC, WSI, LSCD (B,G,C) | 1790–1830 | 1895–1903 | [Schlechtweg et al. (2021)](#paper1) | 2.0.1 |
| DWUG | ES | 100 | 51/24/25 | 40 | 12 | 62k | WiC, WSI, LSCD (B,G,C) | 1810–1906 | 1994–2020 | [Zamora-Reina et al. (2022)](#paper2) | 4.0.0 |
| DiscoWUG | DE | 75 | 39/16/20 | 49 | 8 | 24k | WiC, WSI, LSCD (B,G,C) | 1800–1899 | 1946–1990 | [Kurtyigit et al. (2021)](#paper3) | 1.1.1 |
| RefWUG | DE | 22 | 15/1/6 | 19 | 5 | 4k | WiC, WSI, LSCD (B,G,C) | 1750–1800 | 1850–1900 | ? | 1.1.0 |
| NorDiaChange1 | NO | 40 | 40/0/0 | 21 | 3 | 14k | WiC, WSI, LSCD (B,G,C) | 1929–1965 | 1970–2013 | [Kutuzov et al. (2022)](#paper4) | 1.0.0 |
| NorDiaChange2 | NO | 40 | 40/0/0 | 21 | 3 | 15k | WiC, WSI, LSCD (B,G,C) | 1980–1990 | 2012–2019 | [Kutuzov et al. (2022)](#paper4) | 1.0.0 |
| DURel | DE | 22 | 15/1/6 | 104 | 5 | 6k | WiC, LSCD (C) | 1750–1800 | 1850–1900 | [Schlechtweg et al. (2018)](#paper5) | 3.0.0 |
| SURel | DE | 22 | 19/3/0 | 104 | 4 | 5k | WiC, LSCD (C) | general | domain | [Hätty et al. (2019)](#paper6) | 3.0.0 |
| RuSemShift1 | RU | 71 | 65/6/0 | 119 | 5 | 21k | WiC, LSCD (C) | 1682–1916 | 1918–1990 | [Rodina and Kutuzov (2020)](#paper7) | 2.0.0 |
| RuSemShift2 | RU | 69 | 57/12/0 | 105 | 5 | 18k | WiC, LSCD (C) | 1918–1990 | 1991–2016 | [Rodina and Kutuzov (2020)](#paper7) | 2.0.0 |
| RuShiftEval1 | RU | 111 | 111/0/0 | 60 | 3 | 10k | WiC, LSCD (C) | 1682–1916 | 1918–1990 | [Kutuzov and Pivovarova (2021)](#paper8) | 2.0.0 |
| RuShiftEval2 | RU | 111 | 111/0/0 | 60 | 3 | 10k | WiC, LSCD (C) | 1918–1990 | 1991–2016 | [Kutuzov and Pivovarova (2021)](#paper8) | 2.0.0 |
| RuShiftEval3 | RU | 111 | 111/0/0 | 60 | 3 | 10k | WiC, LSCD (C) | 1682–1916 | 1991–2016 | [Kutuzov and Pivovarova (2021)](#paper8) | 2.0.0 |
LGS = language, n = number of target words, N/V/A = number of nouns/verbs/adjectives, |U| = average number usages per word, AN = number of annotators, JUD = total number of judged usage pairs, Task = possible evaluation tasks, t1, t2 = time period 1/2, Reference = data set reference paper, Version = version used for experiments.
## WUGs
Word Usage Graphs (WUGs) is the graphs displaying the relation between the usage of words. Each usage of word is a node which is connected by the weighted edges. The edges dipict the human-annotated semantic proximity of use pairs. The WUG data set can be found on the [WUGsite](https://www.ims.uni-stuttgart.de/en/research/resources/experiment-data/wugs/).
### Reference
[1]
Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen, Haim Dubossarsky, Barbara McGillivray. 2021. [DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages](https://aclanthology.org/2021.emnlp-main.567/). In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
[2]
Frank D. Zamora-Reina, Felipe Bravo-Marquez, Dominik Schlechtweg. 2022. [LSCDiscovery: A shared task on semantic change discovery and detection in Spanish](https://aclanthology.org/2022.lchange-1.16/). In Proceedings of the 3rd International Workshop on Computational Approaches to Historical Language Change.
[3]
Sinan Kurtyigit, Maike Park, Dominik Schlechtweg, Jonas Kuhn, Sabine Schulte im Walde. 2021. [Lexical Semantic Change Discovery](https://aclanthology.org/2021.acl-long.543/). In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers).
[4]
Andrey Kutuzov, Samia Touileb, Petter Mæhlum, Tita Enstad, and Alexandra Wittemann. 2022. [NorDiaChange: Diachronic Semantic Change Dataset for Norwegian](https://aclanthology.org/2022.lrec-1.274/). In Proceedings of the Thirteenth Language Resources and Evaluation Conference.
[5]
Dominik Schlechtweg, Sabine Schulte im Walde, and Stefanie Eckmann. 2018. [Diachronic Usage Relat
edness (DURel): A framework for the annotation of lexical semantic change.](https://aclanthology.org/N18-2027) In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 169–174.
[6]
Anna Hätty, Dominik Schlechtweg, and Sabine Schulte im Walde. 2019. [SURel: A Gold Standard for Incorporating Meaning Shifts into Term Extraction](https://aclanthology.org/S19-1001). In Proceedings of the 8th Joint Conference on Lexical and Computational Semantics, pages 1–8.
[7]
Julia Rodina and Andrey Kutuzov. 2020. [RuSemShift: a dataset of historical lexical semantic change in Russian](https://aclanthology.org/2020.coling-main.90). In Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020). Association for Computational Linguistics.
[8]
Andrey Kutuzov and Lidia Pivovarova. 2021. Rushifteval: a shared task on semantic shift detection for russian. _Komp’yuternaya Lingvistika i Intellektual’nye Tekhnologii: Dialog conference_.