add post-processing

README.md

@@ -17,16 +17,32 @@ This is a record of German language paraphrases. These are text pairs that have
 The source of the paraphrases are different parallel German / English text corpora.
 The English texts were machine translated back into German. This is how the paraphrases were obtained.
 
+This dataset can be used for example to train semantic text embeddings.
+To do this, for example, [SentenceTransformers](https://www.sbert.net/)
+and the [MultipleNegativesRankingLoss](https://www.sbert.net/docs/package_reference/losses.html#multiplenegativesrankingloss)
+can be used.
+
 ## To-do
 - upload dataset
 - suggest further postprocessing
 - explain dirty "texts" in OpenSubtitles
 
-## Our preprocessing
+## Our pre-processing
 Apart from the back translation, we have added more columns (for details see below). We have carried out the following pre-processing and filtering:
 - We dropped text pairs where one text was longer than 499 characters.
 - In the [GlobalVoices v2018q4](https://opus.nlpl.eu/GlobalVoices-v2018q4.php) texts we have removed the `" · Global Voices"` suffix.
 
+## Your post-processing
+You probably don't want to use the dataset as it is, but filter it further.
+This is what the additional columns of the dataset are for.
+For us it has proven useful to delete the following pairs of sentences:
+
+- `min_char_len < 15`
+- `jaccard_similarity > 0.3`
+- `de_token_count > 30`
+- `en_de_token_count > 30`
+- `cos_sim < .85`
+
 ## Columns description
 - **`uuid`**: a uuid calculated with Python `uuid.uuid4()`
 - **`de`**: the original German texts from the corpus