Update README.md

README.md

@@ -75,11 +75,11 @@ The combined dataset[GIZ/policy_qa_v0_1](https://huggingface.co/datasets/GIZ/pol
 The pre-processing operations used to produce the final training dataset were as follows:
 
 1. Dataset is filtered based on 'medium' value in 'strategy' column (sequence length = 85), selecting only IKITracs samples.
-2. For IKITracs, labels are assigned based on the presence of of 'parameter' values matching the mapping taxonomy defined by TraCS^*
-4. If 'context_translated' is available and the 'language' is not English, 'context' is replaced with 'context_translated'. 
-5. The dataset is "exploded" - i.e., the text samples in the 'context' column, which are lists, are converted into separate rows - and labels are merged to align with the associated samples.
-6. The 'match_onanswer' and 'answerWordcount' are used conditionally to select hihg quality samples (prefers high % of word matches in 'match_onanswer', but will take lower if there is a high 'answerWordcount')
-7. Data is then augmented using sentence shuffle from the ```albumentations``` library
+2. For IKITracs, labels are assigned based on the presence of of 'parameter' values matching the category mapping taxonomy defined by TraCS (ref. below)
+3. If 'context_translated' is available and the 'language' is not English, 'context' is replaced with 'context_translated'. 
+4. The dataset is "exploded" - i.e., the text samples in the 'context' column, which are lists, are converted into separate rows - and labels are merged to align with the associated samples.
+5. The 'match_onanswer' and 'answerWordcount' are used conditionally to select high quality samples (prefers high % of word matches in 'match_onanswer', but will take lower if there is a high 'answerWordcount')
+6. Data is then augmented using sentence shuffle from the ```albumentations``` library and insertions from ```nlpaug```.
 
 ###**Parameter to category mapping taxonomy**
 |index|Category|Parameter|