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  1. README.md +75 -0
  2. test.jsonl +0 -0
  3. train.jsonl +0 -0
  4. validation.jsonl +0 -0
README.md ADDED
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+ ---
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+ language:
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+ - pl
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+ license:
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+ - cc-by-nc-sa-4.0
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10K<n<100K
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+ task_categories:
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+ - text-classification
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+ task_ids:
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+ - topic-classification
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+ - multi-class-classification
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+ pretty_name: 8TAGS
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+ dataset_info:
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+ features:
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+ - name: sentence
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+ dtype: string
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+ - name: label
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+ dtype:
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+ class_label:
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+ names:
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+ 0: film
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+ 1: history
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+ 2: food
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+ 3: medicine
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+ 4: motorization
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+ 5: work
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+ 6: sport
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+ 7: technology
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+ splits:
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+ - name: train
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+ - name: validation
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+ - name: test
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+ ---
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+
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+ # 8TAGS
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+
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+ ### Dataset Summary
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+
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+ A Polish topic classification dataset consisting of headlines from social media posts. It contains about 50,000 sentences annotated with 8 topic labels: film, history, food, medicine, motorization, work, sport and technology. This dataset was created automatically by extracting sentences from headlines and short descriptions of articles posted on Polish social networking site **wykop.pl**. The service allows users to annotate articles with one or more tags (categories). Dataset represents a selection of article sentences from 8 popular categories. The resulting corpus contains cleaned and tokenized, unambiguous sentences (tagged with only one of the selected categories), and longer than 30 characters.
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+
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+ ### Data Instances
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+
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+ Example instance:
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+ ```
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+ {
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+ "sentence": "Kierowca był nieco zdziwiony że podróżując sporo ponad 200 km / h zatrzymali go policjanci.",
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+ "label": "4"
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+ }
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+ ```
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+
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+ ### Data Fields
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+
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+ - sentence: sentence text
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+ - label: label identifier corresponding to one of 8 topics
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+
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+ ### Citation Information
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+
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+ ```
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+ @inproceedings{dadas-etal-2020-evaluation,
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+ title = "Evaluation of Sentence Representations in {P}olish",
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+ author = "Dadas, Slawomir and Pere{\l}kiewicz, Micha{\l} and Po{\'s}wiata, Rafa{\l}",
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+ booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
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+ month = may,
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+ year = "2020",
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+ address = "Marseille, France",
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+ publisher = "European Language Resources Association",
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+ url = "https://aclanthology.org/2020.lrec-1.207",
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+ pages = "1674--1680",
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+ language = "English",
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+ ISBN = "979-10-95546-34-4",
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+ }
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+ ```
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