Update superlim-2.py

superlim-2.py

@@ -101,6 +101,13 @@ The Swedish Word-in-Context dataset provides a benchmark for evaluating distribu
  Word-in-Context dataset, SweWiC consists of 1000 sentence pairs, where each sentence in a pair contains an occurence of a potentially ambiguous focus word specific to that pair. The question posed to the tested 
  system is whether these two occurrences represent instances of the same word sense. There are 500 same-sense pairs and 500 different-sense pairs."""
 
+_argumentation_sentences_DESCRIPTION = """\
+Argumentation sentences is a translated corpus for the task of identifying stance in relation to a topic. It consists of sentences labeled with pro, con or non in relation to one of six topics. 
+The original dataset can be found here https://github.com/trtm/AURC.  The test set is manually corrected translations, the training set is machine translated. """
+
+_argumentation_sentences_DESCRIPTION_CITATION = """\
+"""
+
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
@@ -114,7 +121,8 @@ _TASKS = {
     "swefaq": "SweFAQ",
     "swepar": "SweParaphrase",
     "swesat": "SweSAT-synonyms",
-    "swewic": "SweWIC"
+    "swewic": "SweWIC",
+    "argumentation_sent":"argumentation_sentences"
 }
 
 
@@ -162,7 +170,8 @@ class SuperLim(datasets.GeneratorBasedBuilder):
         datasets.BuilderConfig(name="swefaq", version=VERSION, description=_SweFaq_DESCRIPTION),
         datasets.BuilderConfig(name="swepar", version=VERSION, description=_SwePar_DESCRIPTION),
         datasets.BuilderConfig(name="swesat", version=VERSION, description=_SweSat_DESCRIPTION),
-        datasets.BuilderConfig(name="swewic", version=VERSION, description=_SweWic_DESCRIPTION)
+        datasets.BuilderConfig(name="swewic", version=VERSION, description=_SweWic_DESCRIPTION),
+        datasets.BuilderConfig(name="argumentation_sent", version=VERSION, description=_argumentation_sentences_DESCRIPTION)
     ]
 
     def _info(self):