Update README.md

README.md

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 This is the multilingual parallel dataset for text detoxification prepared for [CLEF TextDetox 2024](https://pan.webis.de/clef24/pan24-web/text-detoxification.html) shared task.
 For each of 9 languages, we collected 1k pairs of toxic<->detoxified instances splitted into two parts: dev (400 pairs) and test (600 pairs). 
 
-**Dev set references and test set toxic sentences will be released later!**
+**Now, only dev set toxic sentences are released. Dev set references and test set toxic sentences will be released later with the test phase of the competition!**
 
 The list of the sources for the original toxic sentences:
 * English: [Jigsaw](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge), [Unitary AI Toxicity Dataset](https://github.com/unitaryai/detoxify)
 * Russian: [Russian Language Toxic Comments](https://www.kaggle.com/datasets/blackmoon/russian-language-toxic-comments), [Toxic Russian Comments](https://www.kaggle.com/datasets/alexandersemiletov/toxic-russian-comments)
 * Ukrainian: [Ukrainian Twitter texts](https://github.com/saganoren/ukr-twi-corpus)
-* Spanish: TBD
+* Spanish: [Detecting and Monitoring Hate Speech in Twitter](https://www.mdpi.com/1424-8220/19/21/4654), [Detoxis](https://rdcu.be/dwhxH), [RoBERTuito: a pre-trained language model for social media text in Spanish](https://aclanthology.org/2022.lrec-1.785/)
 * German: [GemEval 2018, 2021](https://aclanthology.org/2021.germeval-1.1/)
 * Amhairc: [Amharic Hate Speech](https://github.com/uhh-lt/AmharicHateSpeech)
 * Arabic: [OSACT4](https://edinburghnlp.inf.ed.ac.uk/workshops/OSACT4/)