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README.md

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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+task_categories:
+- text-classification
+language:
+- it
+---
+# Dataset Card for AMELIA - Argument Mining Evaluation on Legal documents in ItAlian: A CALAMITA Challenge
+
+This dataset consists of argumentative components extracted from 225 Italian decisions on Value Added Tax, annotated to identify and categorize argumentative text. 
+The proposed tasks consists of three classifications, in the context of argument mining in the legal domain. 
+The objective of the first task is to classify each argumentative component as premise or conclusion, while the second and third tasks aim at classifying the type of premise: legal vs factual, and its corresponding argumentation scheme. 
+
+## Dataset Details
+
+### Dataset Source
+
+- **Repository:** https://github.com/adele-project/AMELIA/
+
+### 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
+
+
+## Citation
+
+**BibTeX:**
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+
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+