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# SumeCzech Corpus |
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These are the accompanying materials of the paper: |
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``` |
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@inproceedings{straka-etal-2018-sumeczech, |
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title = "{S}ume{C}zech: Large {C}zech News-Based Summarization Dataset", |
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author = "Straka, Milan and Mediankin, Nikita and Kocmi, Tom and |
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{\v{Z}}abokrtsk{\'y}, Zden{\v{e}}k and Hude{\v{c}}ek, Vojt{\v{e}}ch and Haji{\v{c}}, Jan", |
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booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC}-2018)", |
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month = may, |
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year = "2018", |
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address = "Miyazaki, Japan", |
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publisher = "European Languages Resources Association (ELRA)", |
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} |
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``` |
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## SumeCzech Download Script |
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To download the SumeCzech dataset, use the `downloader.py` script. |
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The script has several dependencies (and requires an exact version for |
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some of them) listed in `requirements.txt`, you can install them |
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using `pip3 install -r requirements.txt`. |
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You can start the script using `python3 downloader.py`. By default, |
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16 parallel processes are used to download the data (you can |
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override this number using the `--parallel N` option). |
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During download, MD5 hash of every document's headline, abstract and text |
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is checked with the official one, allowing to detect possible errors |
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during download and extraction. Although not recommended, the check |
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can be bypassed by using the `--no_verify_md5` option. |
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The validated documents are saved during download. If the download script |
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is interrupted and run again, it will reuse the already processed |
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documents and only download new ones. |
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### Changelog: |
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- 13 Feb 2018: The original download script was released. |
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- 25 Feb 2023: An update with the following changes: |
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- use the new domain https://data.commoncrawl.org of the CC download; |
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- support Python 3.10 and 3.11, where `collections.Callable` was removed. |
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## SumeCzech ROUGE_RAW Evaluation Metric |
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The RougeRAW metric is implemented in `rouge_raw.py` module, which can |
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compute the RougeRAW-1, RougeRAW-2, RougeRAW-L metrics either for |
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a single pair of documents, or for a pair of corpora. |
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Unfortunately, slightly different tokenization was used in the original |
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paper. Therefore, here we provide the results of the systems from the paper |
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evaluated using the `rouge_raw.py` module. |
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### Results for abstract-headline on test |
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``` |
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RougeRAW-1 RougeRAW-2 RougeRAW-L |
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Method P R F P R F P R F |
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first 13.9 23.6 16.5 04.1 07.4 05.0 12.2 20.7 14.5 |
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random 11.0 17.8 12.8 02.6 04.5 03.1 09.6 15.5 11.1 |
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textrank 13.3 22.8 15.9 03.7 06.8 04.6 11.6 19.9 13.8 |
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t2t 20.2 15.9 17.2 06.7 05.1 05.6 18.6 14.7 15.8 |
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``` |
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### Results for abstract-headline on oodtest |
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``` |
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RougeRAW-1 RougeRAW-2 RougeRAW-L |
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Method P R F P R F P R F |
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first 13.3 26.5 16.7 04.7 10.0 06.0 11.6 23.3 14.7 |
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random 10.6 20.7 13.1 03.2 06.9 04.1 09.3 18.2 11.5 |
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textrank 12.8 25.9 16.3 04.5 09.6 05.7 11.3 22.7 14.2 |
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t2t 19.4 15.1 16.3 07.1 05.2 05.7 18.1 14.1 15.2 |
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``` |
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### Results for text-headline on test |
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``` |
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RougeRAW-1 RougeRAW-2 RougeRAW-L |
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Method P R F P R F P R F |
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first 07.4 13.5 08.9 01.1 02.2 01.3 06.5 11.7 07.7 |
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random 05.9 10.3 06.9 00.5 01.0 00.6 05.2 08.9 06.0 |
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textrank 06.0 16.5 08.3 00.8 02.3 01.1 05.0 13.8 06.9 |
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t2t 08.8 07.0 07.5 00.8 00.6 00.7 08.1 06.5 07.0 |
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``` |
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### Results for text-headline on oodtest |
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``` |
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RougeRAW-1 RougeRAW-2 RougeRAW-L |
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Method P R F P R F P R F |
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first 06.7 13.6 08.3 01.3 02.8 01.6 05.9 12.0 07.4 |
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random 05.2 10.0 06.3 00.6 01.4 00.8 04.6 08.9 05.6 |
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textrank 05.8 16.9 08.1 01.1 03.4 01.5 05.0 14.5 06.9 |
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t2t 06.3 05.1 05.5 00.5 00.4 00.4 05.9 04.8 05.1 |
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``` |
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### Results for text-abstract on test |
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``` |
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RougeRAW-1 RougeRAW-2 RougeRAW-L |
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Method P R F P R F P R F |
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first 13.1 17.9 14.4 01.9 02.8 02.1 08.8 12.0 09.6 |
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random 11.7 15.5 12.7 01.2 01.7 01.3 07.7 10.3 08.4 |
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textrank 11.1 20.8 13.8 01.6 03.1 02.0 07.1 13.4 08.9 |
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t2t 13.2 10.5 11.3 01.2 00.9 01.0 10.2 08.1 08.7 |
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``` |
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### Results for text-abstract on oodtest |
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``` |
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RougeRAW-1 RougeRAW-2 RougeRAW-L |
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Method P R F P R F P R F |
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first 11.1 17.1 12.7 01.6 02.7 01.9 07.6 11.7 08.7 |
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random 10.1 15.1 11.4 01.0 01.7 01.2 06.9 10.3 07.8 |
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textrank 09.8 19.9 12.5 01.5 03.3 02.0 06.6 13.3 08.4 |
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t2t 12.5 09.4 10.3 00.8 00.6 00.6 09.8 07.5 08.1 |
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``` |
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