Update app.py

app.py

@@ -38,13 +38,19 @@ def predict(text):
 markdown_text = '''
 <h1>Structured Sentiment Analysis for Norwegian</h1>
 <p align="left">
-<br>
 This space provides a gradio demo of a <a href="https://huggingface.co/ltg/ssa-perin">pretrained model</a> for structured sentiment analysis (SSA) of Norwegian text, trained on the [NoReC_fine](https://github.com/ltgoslo/norec_fine) dataset by the <a href"https://www.mn.uio.no/ifi/english/research/groups/ltg/">Language Technology Group</a> at the University of Oslo. It implements a method described in the paper <a href="https://aclanthology.org/2022.acl-short.51/">Direct parsing to sentiment graphs</a> by Samuel et al. 2022.
-<br>
-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).
-<br>
+<br><br>
+The model will attempt to identify the following components for a given sentence it deems to be sentiment-bearing: 
+<ul>
+  <li> <it>source expressions</it> (the opinion holder), </li>
+  <li> <it>target expressions</it> (what the opinion is directed towards), </li>
+  <li> <it>polar expressions</it> (the part of the text indicating that an opinion is expressed), </li>
+  <li> and finally the <it>polarity</it> (positive or negative). </li>
+</ul>
+<br><br>
 To download the model and find more in-depth documentation, please see <a href="https://huggingface.co/ltg/ssa-perin">https://huggingface.co/ltg/ssa-perin</a>
 </p>
+<br>
 '''
 
 with gr.Blocks() as demo: