Datasets

This is the Business Scene Dialogue (BSD) dataset, a Japanese-English parallel corpus containing written conversations in various business scenarios. The dataset was construc

This dataset contains two corpora in Spanish and Catalan that consist of annotated Twitter messages for automatic stance detection. The data was collected over 12 days during

Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of composi

The COrpus of Urdu News TExt Reuse (COUNTER) corpus contains 1200 documents with real examples of text reuse from the field of journalism. It has been manually annotated at d

We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the da

The Dutch Book Review Dataset (DBRD) contains over 110k book reviews of which 22k have associated binary sentiment polarity labels. It is intended as a benchmark for sentiment

The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.

Dataset of the eHealth Knowledge Discovery Challenge at IberLEF 2020. It is designed for the identification of semantic entities and relations in Spanish health documents.

EURegIR: Regulatory Compliance IR (EU/UK)

This dataset is intended to advance topic classification for German texts. A classifier that is efffective in English may not be effective in German dataset because it has a h

JFLEG (JHU FLuency-Extended GUG) is an English grammatical error correction (GEC) corpus. It is a gold standard benchmark for developing and evaluating GEC systems with respec

mLAMA: a multilingual version of the LAMA benchmark (T-REx and GoogleRE) covering 53 languages.

The “One Million Posts” corpus is an annotated data set consisting of user comments posted to an Austrian newspaper website (in German language). DER STANDARD is an Austrian

A Persian reading comprehenion task (generating an answer, given a question and a context paragraph). The questions are mined using Google auto-complete, their answers and the

TimeDial presents a crowdsourced English challenge set, for temporal commonsense reasoning, formulated as a multiple choice cloze task with around 1.5k carefully curated dialo

An open, broad-coverage corpus for Finnish named entity recognition presented in Luoma et al. (2020) A Broad-coverage Corpus for Finnish Named Entity Recognition.

We present XLSum, a comprehensive and diverse dataset comprising 1.35 million professionally annotated article-summary pairs from BBC, extracted using a set of carefully desi

This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of MNLI data used in XNLI and state-of-the-art English to Bengali translation model.

The PIRM dataset consists of 200 images, which are divided into two equal sets for validation and testing. These images cover diverse contents, including people, objects, env

This new dataset is designed to solve this great NLP task and is crafted with a lot of care.

This new dataset is designed to solve this great NLP task and is crafted with a lot of care.

This new dataset is designed to solve this great NLP task and is crafted with a lot of care.

This new dataset is designed to solve this great NLP task and is crafted with a lot of care.

A Persian textual entailment task (deciding `sent1` entails `sent2`).

A Persian query paraphrasing task (paraphrase or not, given two questions). The questions are partly mined using Google auto-complete, and partly translated from Quora paraph

A Persian reading comprehenion task (generating an answer, given a question and a context paragraph). The questions are mined using Google auto-complete, their answers and th

A Persian sentiment analysis task (deciding whether a given sentence contains a particular sentiment).

A Persian translation dataset (English -> Persian).

A Persian translation dataset (Persian -> English).