diff --git a/ANALYSIS.md b/ANALYSIS.md
index 2e4c516..e404b84 100644
--- a/ANALYSIS.md
+++ b/ANALYSIS.md
@@ -9,9 +9,9 @@ The baseline SOLOIST is fine-tuned on different data splits to evaluate the perf
 
 The belief state prediction task of SOLOIST utilizes *top-k* and *top-p* sampling to generate the belief state slots and values. Since the baseline SOLOIST uses open-ended generation, it's susceptible to generating random slot-value pairs that are not relevant to the dialog history. Below is an example of how the baseline model generated a slot-value pair that's not relevant to user goals and it completely missed two correct slot-value pairs.
 
-| History | True belief states | Generated belief states |
+| Dialog History | True belief states | Generated belief states |
 | ----- | ----- | ----- |
-|  **user:** we need to find a guesthouse of moderate price. <br  />**system:** do you have any special area you would like to stay?<br/>or possibly a star request for the guesthouse?<br  />**user:** i would like it to have a 3 star rating. | type = guesthouse<br/>pricerange = moderate<br/>stars = 3 | parking = yes<br/>stars = 3 |
+| **user:** we need to find a guesthouse of moderate price.<br  />**system:** do you have any special area you would like to stay?<br/>or possibly a star request for the guesthouse?<br  />**user:** i would like it to have a 3 star rating. | type = guesthouse<br/>pricerange = moderate<br/>stars = 3 | parking = yes<br/>stars = 3 |
 
 
 
@@ -30,15 +30,16 @@ Under low-resource settings, the prompt-based model struggled while generate slo
 | **user:** I need to be picked up from pizza hut city centre after 04:30 | leave = 04:30<br/>departure = pizza hut city centre | arrive = 04:30<br/>destination = pizza hut city centre |
 
 #### Repeated values
-Consider the following example:
+Since value-based prompt generates slots from corresponding values, it can't generate slots for repeated values. Only one slot can be generated for the repeated values. Consider the following example:
 
 | Dialog History | True belief states |  
 | ----- | ----- |
 | **user:** hi, can you help me find a 3 star place to stay?<br />**system:** Is there a particular area or price range you would like?<br />**user:** how about a place in the centre of town that is of type hotel<br />**system:** how long would you like to stay, and how many are in your party?<br />**user:** I'll be arriving saturday and staying for 3 nights. there are 3 of us.| area = centre<br/>stars = 3<br/>type = hotel<br />day = saturday<br/>people = 3<br/>stay = 3|
 
-The repeated value `3` in the above example can lead to ambiguity for value-based prompt while generating the slots. 
+The repeated value `3` in the above example can only generate one slot using value-based prompt, as the word with the highest probability is picked as the generated slot. This suggests that the existing annotations for beleif states doesn't work well with value-based prompt.
 
 #### Multi-prompt methods
+After applying multi-prompt methods like *prompt ensemble* and *prompt augmentation*, the results are similar with just a minor improvement in the JGA scores. Different samples of prompts and answered prompts are applied to value-based prompt, while some yield good results, the others add bias while generating slots and degrade the performance.
 
 #### JGA and JGA* Scores
 Higher JGA* scores suggest the current methods of extracting value candidates need improvements.