Update README.md

README.md

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 - de
 - es
 - tr
+- fr
 pretty_name: MOL
 ---
 # MOL - Context-Aware Multilingual Offensive Lexicon
@@ -18,7 +19,8 @@ It consists of 1,000 explicit and implicit (clue-based) human-annotated rational
 
 For example, the term "stupid" is classified as a context-independent offensive term, as it is predominantly used in pejorative contexts. In contrast, the terms "useless" and "worm" are considered context-dependent offensive terms because they can appear in both non-pejorative contexts—such as "this smartphone is useless" or "the fisherman uses worms for bait"—and pejorative contexts, such as "this last President was useless" or "this human being is such a worm."
 
-Each term and expression in the MOL was annotated by three independent annotators, achieving a high inter-annotator agreement score (73% Kappa). Originally developed in Portuguese, MOL was manually translated by native speakers into English, Spanish, French, German, and Turkish, ensuring cultural adaptations in each language. As a result, MOL is available in six different languages.
+Each term and expression in the MOL was annotated by three independent annotators, achieving a high inter-annotator agreement score (73% Kappa).
+Originally developed in Portuguese, MOL was manually translated by native speakers into English, Spanish, French, German, and Turkish, ensuring cultural adaptations in each language. As a result, MOL is available in six different languages.
 
 
 
@@ -55,3 +57,14 @@ The table below describes the MOL statistics
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+
+# Dataset Description
+- **Proposed by:** Francielle Vargas (<https://franciellevargas.github.io/>)
+- **Funded by:** FAPESP 
+- **Language(s) (NLP):** Portuguese, English, Spanish, French, Germany and Turkish
+- **Repository:** https://github.com/franciellevargas/MOL
+- **Papers:** @article{Vargas_Carvalho_Pardo_Benevenuto_2024, author={Vargas, Francielle and Carvalho, Isabelle and Pardo, Thiago A. S. and Benevenuto, Fabrício}, title={Context-aware and expert data resources for Brazilian Portuguese hate speech detection}, DOI={10.1017/nlp.2024.18}, journal={Natural Language Processing}, year={2024}, pages={1–22}, url={https://www.cambridge.org/core/journals/natural-language-processing/article/contextaware-and-expert-data-resources-for-brazilian-portuguese-hate-speech-detection/7D9019ED5471CD16E320EBED06A6E923#}, }
+
+
+# Dataset Contact
+francielealvargas@gmail.com