Minor modifications

README.md

@@ -128,14 +128,27 @@ to specify the level of quality you desire, such as:
 The entries in the training sets have been ranked automatically by how
 likely they are paraphrases, best first, worst last. The quality
 parameter indicates the estimated proportion (in percent) of true
-paraphrases in the set. Allowed quality values range between 60 and
-100, in increments of 5 (60, 65, 70, ..., 100). A value of 60 means
-that 60% of the sentence pairs in the downloaded set are estimated to
-be true paraphrases (and the remaining 40% are not). A higher value
+paraphrases in the training set. Allowed quality values range between
+60 and 100, in increments of 5 (60, 65, 70, ..., 100). A value of 60
+means that 60% of the sentence pairs in the training set are estimated
+to be true paraphrases (and the remaining 40% are not). A higher value
 produces a smaller but cleaner set. The smaller sets are subsets of
-the larger sets, such that the `quality=95`set is a subset of
+the larger sets, such that the `quality=95` set is a subset of
 `quality=90`, which is a subset of `quality=85`, and so on.
 
+The default `quality` value, if omitted, is 100. This matches no
+training data at all, which can be convenient, if you are only
+interested in the validation and test sets, which are considerably
+smaller, but manually annotated.
+
+Note that an alternative to typing the parameter values explicitly,
+you can use configuration names instead. The following commands are
+equivalent to the ones above:
+
+`data = load_dataset("GEM/opusparcus", "de.100")`
+
+`data = load_dataset("GEM/opusparcus", "fr.90")`
+
 
 ### Data Instances