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README.md

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 The dataset consists of titles and abstracts from NLP-related papers. Each paper is annotated with multiple fields of study from the [NLP taxonomy](#nlp-taxonomy). Each sample is annotated with all possible lower-level concepts and their hypernyms in the [NLP taxonomy](#nlp-taxonomy). The training dataset contains 178,521 weakly annotated samples. The test dataset consists of 828 manually annotated samples from the EMNLP22 conference. The manually labeled test dataset might not contain all possible classes since it consists of EMNLP22 papers only, and some rarer classes haven’t been published there. Therefore, we advise creating an additional test or validation set from the train data that includes all the possible classes.
 
-📄 Paper: [Exploring the Landscape of Natural Language Processing Research (RANLP 2023)](https://aclanthology.org/2023.ranlp-1.111).
+📄 Paper: [Exploring the Landscape of Natural Language Processing Research (RANLP 2023)](https://aclanthology.org/2023.ranlp-1.111)
 
 💻 Code: [https://github.com/sebischair/Exploring-NLP-Research](https://github.com/sebischair/Exploring-NLP-Research)