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35 dataset results for Polish

The Universal Dependencies (UD) project seeks to develop cross-linguistically consistent treebank annotation of morphology and syntax for multiple languages. The first version of the dataset was released in 2015 and consisted of 10 treebanks over 10 languages. Version 2.7 released in 2020 consists of 183 treebanks over 104 languages. The annotation consists of UPOS (universal part-of-speech tags), XPOS (language-specific part-of-speech tags), Feats (universal morphological features), Lemmas, dependency heads and universal dependency labels.

480 PAPERS • 15 BENCHMARKS

Common Voice

Common Voice is an audio dataset that consists of a unique MP3 and corresponding text file. There are 9,283 recorded hours in the dataset. The dataset also includes demographic metadata like age, sex, and accent. The dataset consists of 7,335 validated hours in 60 languages.

210 PAPERS • 262 BENCHMARKS

OpenSubtitles

OpenSubtitles is collection of multilingual parallel corpora. The dataset is compiled from a large database of movie and TV subtitles and includes a total of 1689 bitexts spanning 2.6 billion sentences across 60 languages.

190 PAPERS • 1 BENCHMARK

Europarl

Europarl (European Parliament Proceedings Parallel Corpus)

A corpus of parallel text in 21 European languages from the proceedings of the European Parliament.

126 PAPERS • NO BENCHMARKS YET

CC100

This corpus comprises of monolingual data for 100+ languages and also includes data for romanized languages. This was constructed using the urls and paragraph indices provided by the CC-Net repository by processing January-December 2018 Commoncrawl snapshots. Each file comprises of documents separated by double-newlines and paragraphs within the same document separated by a newline. The data is generated using the open source CC-Net repository.

72 PAPERS • NO BENCHMARKS YET

Europarl-ST

Europarl-ST is a multilingual Spoken Language Translation corpus containing paired audio-text samples for SLT from and into 9 European languages, for a total of 72 different translation directions. This corpus has been compiled using the debates held in the European Parliament in the period between 2008 and 2012.

45 PAPERS • NO BENCHMARKS YET

OSCAR

OSCAR or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy architecture. The dataset used for training multilingual models such as BART incorporates 138 GB of text.

42 PAPERS • NO BENCHMARKS YET

WikiAnn

WikiAnn is a dataset for cross-lingual name tagging and linking based on Wikipedia articles in 295 languages.

33 PAPERS • 7 BENCHMARKS

WMT 2020

WMT 2020 is a collection of datasets used in shared tasks of the Fifth Conference on Machine Translation. The conference builds on a series of annual workshops and conferences on Statistical Machine Translation.

31 PAPERS • 1 BENCHMARK

MKQA (Multilingual Knowledge Questions and Answers)

Multilingual Knowledge Questions and Answers (MKQA) is an open-domain question answering evaluation set comprising 10k question-answer pairs aligned across 26 typologically diverse languages (260k question-answer pairs in total). The goal of this dataset is to provide a challenging benchmark for question answering quality across a wide set of languages. Answers are based on a language-independent data representation, making results comparable across languages and independent of language-specific passages. With 26 languages, this dataset supplies the widest range of languages to-date for evaluating question answering.

30 PAPERS • NO BENCHMARKS YET

MULTEXT-East

The MULTEXT-East resources are a multilingual dataset for language engineering research and development. It consists of the (1) MULTEXT-East morphosyntactic specifications, defining categories (parts-of-speech), their morphosyntactic features (attributes and values), and the compact MSD tagset representations; (2) morphosyntactic lexica, (3) the annotated parallel "1984" corpus; and (4) some comparable text and speech corpora. The specifications are available for the following macrolanguages, languages and language varieties: Albanian, Bulgarian, Chechen, Czech, Damaskini, English, Estonian, Hungarian, Macedonian, Persian, Polish, Resian, Romanian, Russian, Serbo-Croatian, Slovak, Slovene, Torlak, and Ukrainian, while the other resources are available for a subset of these languages.

22 PAPERS • NO BENCHMARKS YET

XGLUE

XGLUE is an evaluation benchmark XGLUE,which is composed of 11 tasks that span 19 languages. For each task, the training data is only available in English. This means that to succeed at XGLUE, a model must have a strong zero-shot cross-lingual transfer capability to learn from the English data of a specific task and transfer what it learned to other languages. Comparing to its concurrent work XTREME, XGLUE has two characteristics: First, it includes cross-lingual NLU and cross-lingual NLG tasks at the same time; Second, besides including 5 existing cross-lingual tasks (i.e. NER, POS, MLQA, PAWS-X and XNLI), XGLUE selects 6 new tasks from Bing scenarios as well, including News Classification (NC), Query-Ad Matching (QADSM), Web Page Ranking (WPR), QA Matching (QAM), Question Generation (QG) and News Title Generation (NTG). Such diversities of languages, tasks and task origin provide a comprehensive benchmark for quantifying the quality of a pre-trained model on cross-lingual natural lan

14 PAPERS • 3 BENCHMARKS

X-Fact

X-FACT is a large publicly available multilingual dataset for factual verification of naturally existing real-world claims. The dataset contains short statements in 25 languages and is labeled for veracity by expert fact-checkers. The dataset includes a multilingual evaluation benchmark that measures both out-of-domain generalization, and zero-shot capabilities of the multilingual models.

9 PAPERS • 1 BENCHMARK

KLEJ

The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding task.

8 PAPERS • NO BENCHMARKS YET

XQA

XQA is a data which consists of a total amount of 90k question-answer pairs in nine languages for cross-lingual open-domain question answering.

6 PAPERS • NO BENCHMARKS YET

MultiEURLEX

MultiEURLEX is a multilingual dataset for topic classification of legal documents. The dataset comprises 65k European Union (EU) laws, officially translated in 23 languages, annotated with multiple labels from the EUROVOC taxonomy. The dataset covers 23 official EU languages from 7 language families.

5 PAPERS • NO BENCHMARKS YET

Concepticon (Concepticon. A Resource for the Linking of Concept Lists)

This resource, our Concepticon, links concept labels from different conceptlists to concept sets. Each concept set is given a unique identifier, a unique label, and a human-readable definition. Concept sets are further structured by defining different relations between the concepts, as you can see in the graphic to the right, which displays the relations between concept sets linked to the concept set SIBLING. The resource can be used for various purposes. Serving as a rich reference for new and existing databases in diachronic and synchronic linguistics, it allows researchers a quick access to studies on semantic change, cross-linguistic polysemies, and semantic associations.

4 PAPERS • NO BENCHMARKS YET

MuMiN

MuMiN is a misinformation graph dataset containing rich social media data (tweets, replies, users, images, articles, hashtags), spanning 21 million tweets belonging to 26 thousand Twitter threads, each of which have been semantically linked to 13 thousand fact-checked claims across dozens of topics, events and domains, in 41 different languages, spanning more than a decade.

4 PAPERS • 3 BENCHMARKS

GeoCoV19

GeoCoV19 is a large-scale Twitter dataset containing more than 524 million multilingual tweets. The dataset contains around 378K geotagged tweets and 5.4 million tweets with Place information. The annotations include toponyms from the user location field and tweet content and resolve them to geolocations such as country, state, or city level. In this case, 297 million tweets are annotated with geolocation using the user location field and 452 million tweets using tweet content.

3 PAPERS • NO BENCHMARKS YET

WikiNEuRal

WikiNEuRal is a high-quality automatically-generated dataset for Multilingual Named Entity Recognition.

3 PAPERS • NO BENCHMARKS YET

Allegro Reviews

A comprehensive multi-task benchmark for the Polish language understanding, accompanied by an online leaderboard. It consists of a diverse set of tasks, adopted from existing datasets for named entity recognition, question-answering, textual entailment, and others.

2 PAPERS • NO BENCHMARKS YET

EUR-Lex-Sum

EUR-Lex-Sum is a dataset for cross-lingual summarization. It is based on manually curated document summaries of legal acts from the European Union law platform. Documents and their respective summaries exist as crosslingual paragraph-aligned data in several of the 24 official European languages, enabling access to various cross-lingual and lower-resourced summarization setups. The dataset contains up to 1,500 document/summary pairs per language, including a subset of 375 cross-lingually aligned legal acts with texts available in all 24 languages.

2 PAPERS • NO BENCHMARKS YET

Multilingual Dataset for Training and Evaluating Diacritics Restoration Systems

The dataset contains training and evaluation data for 12 languages: - Vietnamese - Romanian - Latvian - Czech - Polish - Slovak - Irish - Hungarian - French - Turkish - Spanish - Croatian

2 PAPERS • 12 BENCHMARKS

Tilde MODEL Corpus

Tilde MODEL Corpus (Tilde Multilingual Open Data for European Languages)

Tilde MODEL Corpus is a multilingual corpora for European languages – particularly focused on the smaller languages. The collected resources have been cleaned, aligned, and formatted into a corpora standard TMX format useable for developing new Language technology products and services.

2 PAPERS • NO BENCHMARKS YET

Demetr

Demetr is a diagnostic dataset with 31K English examples (translated from 10 source languages) for evaluating the sensitivity of MT evaluation metrics to 35 different linguistic perturbations spanning semantic, syntactic, and morphological error categories.

1 PAPER • NO BENCHMARKS YET

EVI

The EVI dataset is a challenging, multilingual spoken-dialogue dataset with 5,506 dialogues in English, Polish, and French. The dataset can be used to develop and benchmark conversational systems for user authentication tasks, i.e. speaker enrolment (E), speaker verification (V), speaker identification (I).

1 PAPER • 3 BENCHMARKS

EventEA

EventEA is an event-centric entity alignment dataset, harvested from EventKG, DBpedia and Wikidata.

1 PAPER • NO BENCHMARKS YET

LEPISZCZE

LEPISZCZE is an open-source comprehensive benchmark for Polish NLP and a continuous-submission leaderboard, concentrating public Polish datasets (existing and new) in specific tasks.

1 PAPER • NO BENCHMARKS YET

M-AILabs speech dataset

The M-AILABS Speech Dataset is the first large dataset that we are providing free-of-charge, freely usable as training data for speech recognition and speech synthesis. Most of the data is based on LibriVox and Project Gutenberg. The training data consist of nearly thousand hours of audio and the text-files in prepared format. A transcription is provided for each clip. Clips vary in length from 1 to 20 seconds and have a total length of approximately shown in the list (and in the respective info.txt-files) below. The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded by the LibriVox project and is also in the public domain

1 PAPER • 1 BENCHMARK

Mega-COV

Mega-COV is a billion-scale dataset from Twitter for studying COVID-19. The dataset is diverse (covers 234 countries), longitudinal (goes as back as 2007), multilingual (comes in 65 languages), and has a significant number of location-tagged tweets (~32M tweets).

1 PAPER • NO BENCHMARKS YET

MultiTACRED

MultiTACRED is a multilingual version of the large-scale TAC Relation Extraction Dataset. It covers 12 typologically diverse languages from 9 language families, and was created by the Speech & Language Technology group of DFKI by machine-translating the instances of the original TACRED dataset and automatically projecting their entity annotations. For details of the original TACRED's data collection and annotation process, see the Stanford paper. Translations are syntactically validated by checking the correctness of the XML tag markup. Any translations with an invalid tag structure, e.g. missing or invalid head or tail tag pairs, are discarded (on average, 2.3% of the instances).

1 PAPER • NO BENCHMARKS YET

Multilingual Terms of Service

The first annotated corpus for multilingual analysis of potentially unfair clauses in online Terms of Service. The data set comprises a total of 100 contracts, obtained from 25 documents annotated in four different languages: English, German, Italian, and Polish. For each contract, potentially unfair clauses for the consumer are annotated, for nine different unfairness categories.

1 PAPER • NO BENCHMARKS YET

Polish CDSCorpus

Consists of 10K sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of compositional distributional semantics models of Polish.

1 PAPER • NO BENCHMARKS YET

Polish Political Advertising Dataset

A dataset for detecting specific text chunks and categories of political advertising in the Polish language. It contains 1,705 human-annotated tweets tagged with nine categories, which constitute campaigning under Polish electoral law.

1 PAPER • NO BENCHMARKS YET

SEN

SEN (Sentiment analysis of Entities in News headlines)

SEN is a novel publicly available human-labelled dataset for training and testing machine learning algorithms for the problem of entity level sentiment analysis of political news headlines.

0 PAPER • NO BENCHMARKS YET

Datasets

35 dataset results for Polish