extended readme

README.md

@@ -13,6 +13,14 @@ Publications using this dataset must include a reference to the following public
 SeCoDa: Sense Complexity Dataset. David Strohmaier, Sian Gooding, Shiva Taslimipoor, Ekaterina Kochmar. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 5964–5969, Marseille, 11–16 May 2020
 </pre>
 
+The dataset is based on the earlier CWIG3G2 dataset, see the [paper](https://aclanthology.org/I17-2068.pdf) and [website](https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/complex-word-identification-dataset.html). The relevant citation is
+
+<pre>
+Seid Muhie Yimam, Sanja Štajner, Martin Riedl, and Chris Biemann (2017): CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups. In Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP 2017). Taipei, Taiwan
+</pre>
+
+The complexity data can be found in the CWIG3G2 dataset and combined with the senses provided by SeCoDa. 
+
 # Repository Content
 
 Main data are found in SeCoDa.tsv. The columns are structured as follows.
@@ -35,7 +43,9 @@ Example:
 
 The senses are drawn from the [Cambridge Advanced Learner's Dictionary](https://dictionary.cambridge.org).
 
-*UPDATE* Two missing entries have been added and typos in comments have been corrected.
+*UPDATE*: Two missing entries have been added and typos in comments have been corrected.
+
+*UPDATE*: Added further information to readme.
 
 This work is licensed under a [Creative Commons Attribution-NonCommerial-ShareAlike 4.0
 International License][cc-by-nc-sa].