Update README.md

README.md

@@ -20,19 +20,35 @@ The objective of the first task is to classify each argumentative component as p
 ### Dataset Structure
 
 The dataset consists of the following columns:
-• Text: the text of the argumentative component
-• Document: the document it belongs to
-• Component: if it is a premise (prem) or a conclusion (conc)
-• Type: a list value representing the type of a premise; the list contains F for a Factual premise and L for a Legal one.
-• Scheme: a list value representing the argumentative schemes of a legal premise. The values are: Rule, Prec, Class, Itpr and Princ.
-• Chain_id: univocal for each document, it specifies the argumentative chain the component belongs to (e.g. A1, A2,..., B1, B2,...)
-• Id: an univocal numerical id
+- Text: the text of the argumentative component
+- Document: the document it belongs to
+- Component: if it is a premise (prem) or a conclusion (conc)
+- Type: a list value representing the type of a premise; the list contains F for a Factual premise and L for a Legal one.
+- Scheme: a list value representing the argumentative schemes of a legal premise. The values are: Rule, Prec, Class, Itpr and Princ.
+- Chain_id: univocal for each document, it specifies the argumentative chain the component belongs to (e.g. A1, A2,..., B1, B2,...)
+- Id: an univocal numerical id
 
 
 ## Citation
 
 **BibTeX:**
 
+@inproceedings{
+  author       = {Giulia Grundler and
+                  Andrea Galassi and
+                  Piera Santin and
+                  Alessia Fidangeli and
+                  Federico Galli and
+                  Elena Palmieri and
+                  Francesca Lagioia and
+                  Giovanni Sartor and 
+                  Paolo Torroni},
+  title        = {AMELIA - Argument Mining Evaluation on Legal documents in ItAlian: A CALAMITA Challenge},
+  booktitle    = {Proceedings of CLiC-it 2024: Tenth Italian Conference on Computational Linguistics},
+  year         = {},
+  doi          = {},
+}
+