Update README.md

README.md

@@ -53,7 +53,7 @@ We here release a pretrained model (and an easy-to-run wrapper) for structured s
 ## How to Get Started with the Model
 
 
-The model will attempt to identify the following components for a given sentence it deems to be sentiment-bearing: _source expressions_ (the opinion holder), _target expressions_ (what the opinion is directed towards), _polar expressions_ (the part of the text indicating that an opinion is expressed), and finally the _polarity_ (positive or negative). For more information about how these categories are defined in the training data, please the paper [A Fine-grained Sentiment Dataset for Norwegian](https://aclanthology.org/2020.lrec-1.618/) by Øvrelid et al. 2020. For each identified expression, the character offsets in the text are also provided.
+The model will attempt to identify the following components for a given sentence it deems to be sentiment-bearing: _source expressions_ (the opinion holder), _target expressions_ (what the opinion is directed towards), _polar expressions_ (the part of the text indicating that an opinion is expressed), and finally the _polarity_ (positive or negative). For more information about how these categories are defined in the training data, please see the paper [A Fine-grained Sentiment Dataset for Norwegian](https://aclanthology.org/2020.lrec-1.618/) by Øvrelid et al. 2020. For each identified expression, the character offsets in the text are also provided.
 
 Here is an example showing how to use the model for predicting such sentiment tuples: