Update README.md

README.md

@@ -38,4 +38,28 @@ The dataset consists of 5500 English sentence pairs that are scored and ranked o
 - Additionally:
   - the SourceID column indicates the source dataset from which the sentence pair was drawn (see Table 2 of our paper)
   - The SubsetID column indicates the sampling strategy used for the source dataset
-  - and the PairID is a unique identifier for each pair that also indicates its Source and Subset.
+  - and the PairID is a unique identifier for each pair that also indicates its Source and Subset.
+ 
+### Citing our work 
+Please use the following BibTex entry to cite us if you use our dataset or any of the associated analyses:
+
+```
+@inproceedings{abdalla2021makes,
+      title={What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study},
+      author={Abdalla, Mohamed and Vishnubhotla, Krishnapriya and Mohammad, Saif M.},
+      year={2023},
+      address = {Dubrovnik, Croatia},
+      publisher = "Association for Computational Linguistics",
+      booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume"
+}
+```
+
+## Ethics Statement
+Any dataset of semantic relatedness entails several ethical considerations. We talk about this in Section 8 of our paper.
+
+## Creators
+- [Mohamed Abdalla](https://www.cs.toronto.edu/~msa/index_all.html) (University of Toronto)
+- [Krishnapriya Vishnubhotla](https://priya22.github.io/) (University of Toronto)
+- [Saif M. Mohammad](http://saifmohammad.com/) (National Research Council Canada)
+
+**Contact**: msa@cs.toronto.edu, vkpriya@cs.toronto.edu, saif.mohammad@nrc-cnrc.gc.ca