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--- |
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dataset_info: |
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features: |
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- name: id |
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dtype: string |
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- name: url |
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dtype: string |
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- name: crawled |
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dtype: string |
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- name: hard |
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dtype: bool |
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- name: paragraphs |
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list: |
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- name: text |
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dtype: string |
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- name: duplicate |
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dtype: bool |
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- name: keep |
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dtype: bool |
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- name: primary_level_1 |
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dtype: string |
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- name: primary_level_2 |
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dtype: string |
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- name: primary_level_3 |
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dtype: string |
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- name: secondary_level_1 |
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dtype: string |
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- name: secondary_level_2 |
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dtype: string |
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- name: secondary_level_3 |
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dtype: string |
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- name: tertiary_level_1 |
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dtype: string |
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- name: tertiary_level_2 |
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dtype: string |
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- name: tertiary_level_3 |
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dtype: string |
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- name: split |
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dtype: string |
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- name: domain |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 2250345 |
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num_examples: 602 |
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- name: validation |
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num_bytes: 657986 |
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num_examples: 200 |
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- name: test |
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num_bytes: 550742 |
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num_examples: 200 |
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download_size: 1424443 |
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dataset_size: 3459073 |
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license: |
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- cc-by-sa-4.0 |
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language: |
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- sl |
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multilinguality: |
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- monolingual |
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task_categories: |
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- text-classification |
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size_categories: |
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- 1K<n<10K |
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--- |
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|
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# Dataset Card for Ginco |
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### Dataset Summary |
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The Slovene Web genre identification corpus GINCO 1.0 contains 1,002 web texts (478,969 words), manually annotated with genres. |
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The corpus allows for automated genre identification and genre analyses as well as other web corpora research. |
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This dataset was extracted from the manually-annotated subcorpus (GINCO-1.0-suitable.json.zip) from the original GINCO dataset, |
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published on the [CLARIN.SI repository](http://hdl.handle.net/11356/1467). |
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The dataset is split into 602 training, 200 validation, and 200 test texts by the original authors. |
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The texts in the suitable subset are annotated with up to three genre categories, |
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where the primary label is the most prevalent, and secondary and tertiary labels denote presence of additional genre(s). |
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The secondary and tertiary labels are available for multilabel classification, |
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while for most use cases, we suggest that only the primary label is used. |
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The labels are provided in three levels of detail (three category sets), allowing experiments with the full set (24 labels), |
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set of 21 labels (labels with less than 5 instances are merged with label Other) and set of 12 labels (similar labels are merged). |
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For most use cases, we suggest that the smallest set -- set of 12 labels is used (`primary_level_3`), |
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and that the category "Other" is regarded as a "throw-away" category to detect texts |
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for which the classifier could not predict any of the concrete labels. |
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Additionally, the corpus contains some metadata about the text (e.g. url, domain, year) |
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and its paragraphs (e.g. near-duplicates and their usefulness for the genre identification). |
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More details on dataset construction, manual annotation and results of machine learning experiments |
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are provided in the paper ["The GINCO Training Dataset for Web Genre Identification of Documents Out in the Wild"](https://aclanthology.org/2022.lrec-1.170/) (Kuzman et al., 2022). |
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### Languages |
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Slovenian. |
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## Dataset Structure |
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### Data Instances |
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A sample instance from the dataset: |
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``` |
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{ |
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"id": "3776", |
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"url": "http://www.radiocelje.si/novica.php?id=13007&m=11&l=2010", |
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"crawled": "2014", |
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"hard": false, |
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"paragraphs": [ |
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{ |
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"text": "V novembru, mesecu prepre\u010devanja odvisnosti, bodo \u010dlani Lokalne akcijske skupine za prepre\u010devanje zasvojenosti izvedli niz strokovnih predavanj za star\u0161e osnovno\u0161olcev v Celju...", |
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"duplicate": false, |
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"keep": true |
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}, |
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{ |
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"text": "Predavanja, ki jih bodo ta mesec organizirali na devetih osnovnih \u0161olah v mestni ob\u010dini Celje, so namenjena star\u0161em u\u010dencev od \u0161estega do devetega razreda. Program predavanj finan\u010dno podpira Mestna ob\u010dina Celje. Osrednja tema predavanj bodo varovalni dejavniki vzgoje, ki lahko pripomorejo k neuporabi drog. Po drogah, dovoljenih in nedovoljenih namre\u010d vse pogosteje posegajo \u017ee otroci. Na predavanjih se bodo star\u0161i seznanili tudi z informacijami o tem, na katere vedenjske in telesne spremembe naj bodo pozorni, kadar sumijo, da je otrok posegel po drogi. \u010ceprav je tema aktualna, saj poleg problemov odvisnosti osvetljuje ve\u0161\u010dine u\u010dinkovitega star\u0161evstva in komuniciranja z otroki v konfliktnih situacijah, se je lani ciklusa predavanj na osmih osnovnih \u0161olah udele\u017eilo le 160 star\u0161ev. Organizatorji tokrat upajo na bolj\u0161i odziv. Niz predavanj bodo izvedli strokovnjaki s podro\u010dja medicine, psihologije, socialnega dela in kriminologije. (ba)", |
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"duplicate": false, |
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"keep": true |
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} |
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], |
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"primary_level_1": "News/Reporting", |
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"primary_level_2": "News/Reporting", |
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"primary_level_3": "News/Reporting", |
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"secondary_level_1": "", |
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"secondary_level_2": "", |
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"secondary_level_3": "", |
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"tertiary_level_1": "", |
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"tertiary_level_2": "", |
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"tertiary_level_3": "", |
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"split": "train", |
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"domain": "www.radiocelje.si" |
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} |
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``` |
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### Data Fields |
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- 'id': id of the example; |
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- 'url': exact URL from where the text originates; |
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- 'crawled': the year, when the text has been obtained from the stated URL; |
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- 'hard': whether it was difficult for a human to assign a genre to the text; |
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- 'paragraphs': |
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- 'text': text of the paragraph; |
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- 'duplicate': true if the text is a near-duplicate; |
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- 'keep': true, if the text is useful for the genre identification, false, if not; |
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- 'primary_level_1': first genre category, most detailed category set; |
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- 'primary_level_2': first genre category, category set where too infrequent categories are merged to Other; |
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- 'primary_level_3': first genre category, compact and most useful category set; |
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- 'secondary_level_1': second genre category, most detailed category set; |
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- 'secondary_level_2': second genre category, category set where too infrequent categories are merged to Other; |
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- 'secondary_level_3': second genre category, compact and most useful category set; |
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- 'tertiary_level_1': third genre category, most detailed category set; |
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- 'tertiary_level_2': third genre category, category set where too infrequent categories are merged to Other; |
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- 'tertiary_level_3': third genre category, compact and most useful category set; |
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- 'split': example can belong to the 'train', 'dev', or 'test' split; |
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- 'domain': domain address of the website where the text originates from. |
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#### Genre categories |
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Texts are annotated using 24 genre categories: |
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- News/Reporting, |
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- Announcement, |
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- Research Article, |
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- Instruction, |
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- Recipe, |
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- Call (such as a Call for Papers), |
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- Legal/Regulation, |
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- Information/Explanation, |
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- Opinionated News, |
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- Review, |
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- Opinion/Argumentation, |
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- Promotion of a Product, |
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- Promotion of Services, |
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- Invitation, |
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- Promotion, |
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- Interview, |
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- Forum, |
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- Correspondence, |
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- Script/Drama, |
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- Prose, |
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- Lyrical, |
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- FAQ (Frequently Asked Questions), |
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- List of Summaries/Excerpts, |
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- Other. |
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See the [Appendix in the paper](https://aclanthology.org/2022.lrec-1.170/) for descriptions of the labels. |
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## Additional Information |
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### Dataset Curators |
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Kuzman, Taja ; Brglez, Mojca ; Rupnik, Peter and Ljubešić, Nikola |
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### Licensing Information |
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CC BY-SA 4.0 |
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### Citation Information |
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To cite the dataset: |
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``` |
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@misc{11356/1467, |
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title = {Slovene Web genre identification corpus {GINCO} 1.0}, |
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author = {Kuzman, Taja and Brglez, Mojca and Rupnik, Peter and Ljube{\v s}i{\'c}, Nikola}, |
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url = {http://hdl.handle.net/11356/1467}, |
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note = {Slovenian language resource repository {CLARIN}.{SI}}, |
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copyright = {Creative Commons - Attribution-{ShareAlike} 4.0 International ({CC} {BY}-{SA} 4.0)}, |
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issn = {2820-4042}, |
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year = {2021} |
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} |
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``` |
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To cite the paper on the dataset construction and manual annotation: |
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``` |
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@inproceedings{kuzman2022ginco, |
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title={The GINCO Training Dataset for Web Genre Identification of Documents Out in the Wild}, |
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author={Kuzman, Taja and Rupnik, Peter and Ljube{\v{s}}i{\'c}, Nikola}, |
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booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference}, |
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pages={1584--1594}, |
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year={2022} |
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} |
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``` |
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### Contributions |
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Thanks to Hana Skitek for adding this dataset, and Taja Kuzman for extending the readme with additional information on the dataset. |
