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README.md

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-## Dataset Summary
 
-A dataset for benchmarking keyphrase extraction and generation techniques from english news articles. For more details about the dataset please refer the original paper - [https://dl.acm.org/doi/10.5555/1859664.1859668](https://dl.acm.org/doi/10.5555/1859664.1859668)
+A dataset for benchmarking keyphrase extraction and generation techniques from long document english scientific articles. For more details about the dataset please refer the original paper - [https://dl.acm.org/doi/10.5555/1859664.1859668](https://dl.acm.org/doi/10.5555/1859664.1859668)
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+Original source of the data - [https://github.com/boudinfl/semeval-2010-pre](https://github.com/boudinfl/semeval-2010-pre)
+
+## Dataset Summary
+The Semeval-2010 dataset was originally proposed by *Su Nam Kim et al* in the paper titled - [SemEval-2010 Task 5: Automatic Keyphrase Extraction from Scientific Articles](https://aclanthology.org/S10-1004.pdf) in the year 2010. The dataset consists of a set of 284 English scientific papers from the ACM Digital Library (conference and work-shop papers). The selected articles belong to the
+following four 1998 ACM classifications: C2.4 (Distributed Systems), H3.3 (Information Search and Retrieval), I2.11 (Distributed Artificial Intelligence – Multiagent Systems) and J4 (Socialand Behavioral Sciences – Economics). Each paper has two sets of keyphrases annotated by readers and author. The original dataset was divided into trail, training and test splits, evenly distributed across four domains. The trial, training and test splits had 40, 144 and 100 articles respectively, and the trial split was a subset of training split. We provide test and train splits with 100 and 144 articles respectively.
 
-Original source of the data - [https://github.com/LIAAD/KeywordExtractor-Datasets/blob/master/datasets/SemEval2010.zip](https://github.com/LIAAD/KeywordExtractor-Datasets/blob/master/datasets/SemEval2010.zip)
+ The dataset shared over here categorizes the keyphrases into *extractive* and *abstractive*. **Extractive keyphrases** are those that could be found in the input text and the **abstractive keyphrases** are those that are not present in the input text. In order to get all the meta-data about the documents and keyphrases please refer to the [original source](https://github.com/boudinfl/semeval-2010-pre) from which the dataset was taken from. The main motivation behind making this dataset available in the form as presented over here is to make it easy for the researchers to programmatically download it and evaluate their models for the tasks of keyphrase extraction and generation. As keyphrase extraction by treating it as a sequence tagging task and using contextual language models has become popular - [Keyphrase extraction from scholarly articles as sequence labeling using contextualized embeddings](https://arxiv.org/pdf/1910.08840.pdf), we have also made the token tags available in the BIO tagging format.   
 
 
 ## Dataset Structure