Update README.md

README.md

@@ -34,6 +34,27 @@ The `knowgl-large` model is trained by combining Wikidata with an extended versi
 ```
 If there are more than one triples generated, they are separated by `$` in the output.
 
-The model achieves state-of-the-art results for relation extraction on the test dataset of REBEL. See results comparison with [GenIE (Josifoski et al (NAACL 2022))](https://aclanthology.org/2022.naacl-main.342.pdf) in [Mihindukulasooriya et al (ISWC 2022)](https://arxiv.org/pdf/2207.05188.pdf).
+The model achieves state-of-the-art results for relation extraction on the test dataset of REBEL. See results in [Mihindukulasooriya et al (ISWC 2022)](https://arxiv.org/pdf/2207.05188.pdf).
 
-The generated labels (for subject, relation and object) and types (subject and object) can be directly mapped to Wikidata IDs associated with them.
+The generated labels (for subject, relation and object) and types (subject and object) can be directly mapped to Wikidata IDs associated with them.
+
+#### Citation
+```bibtex
+@article{DBLP:journals/corr/abs-2207-05188,
+  author    = {Nandana Mihindukulasooriya and
+               Mike Sava and
+               Gaetano Rossiello and
+               Md. Faisal Mahbub Chowdhury and
+               Irene Yachbes and
+               Aditya Gidh and
+               Jillian Duckwitz and
+               Kovit Nisar and
+               Michael Santos and
+               Alfio Gliozzo},
+  title     = {Knowledge Graph Induction enabling Recommending and Trend Analysis:
+               {A} Corporate Research Community Use Case},
+  journal   = {CoRR},
+  volume    = {abs/2207.05188},
+  year      = {2022}
+}
+```