minor update

Author: changliu2

articles/ai-studio/how-to/develop/evaluate-sdk.md

@@ -61,7 +61,7 @@ Built-in evaluators can accept *either* query and response pairs or a list of co
 | Evaluator       | `query`      | `response`      | `context`       | `ground_truth`  | `conversation` |
 |----------------|---------------|---------------|---------------|---------------|-----------|
 |`GroundednessEvaluator`   | Optional: String | Required: String | Required: String | N/A  | Supported for text |
-| `GroundednessProEvaluator`   | Required: String | Required: String | Required: String | N/A  | Supported for text |
+| `GroundednessProEvaluator`  | Required: String | Required: String | Required: String | N/A  | Supported for text |
 | `RetrievalEvaluator`        | Required: String | N/A | Required: String         | N/A           | Supported for text |
 | `RelevanceEvaluator`      | Required: String | Required: String | N/A | N/A           | Supported for text |
 | `CoherenceEvaluator`      | Required: String | Required: String | N/A           | N/A           |Supported for text |
@@ -79,7 +79,7 @@ Built-in evaluators can accept *either* query and response pairs or a list of co
 | `IndirectAttackEvaluator`      | Required: String | Required: String | Required: String | N/A           |Supported for text |
 | `ProtectedMaterialEvaluator`  | Required: String | Required: String | N/A           | N/A           |Supported for text and image |
 | `QAEvaluator`      | Required: String | Required: String | Required: String | Required: String           | Not supported |
-| `ContentSafetyEvaluator`      | Required: String | Required: String |  N/A  | N/A           | Supported for text and image |
+| `ContentSafetyEvaluator`     | Required: String | Required: String |  N/A  | N/A           | Supported for text and image |
 
 - Query: the query sent in to the generative AI application
 - Response: the response to the query generated by the generative AI application
@@ -295,9 +295,10 @@ The result of the AI-assisted quality evaluators for a query and response pair i
 - `{metric_name}_label` provides a binary label.
 - `{metric_name}_reason` explains why a certain score or label was given for each data point.
 
+#### Comparing quality and custom evaluators
 For NLP evaluators, only a score is given in the `{metric_name}` key.
 
-Like 6 other AI-assisted evaluators, `GroundednessEvaluator` is a prompt-based evaluator that outputs a score on a 5-point scale (the higher the score, the more grounded the result is). On the other hand, `GroundednessProEvaluator` invokes our backend evaluation service powered by Azure AI Content Safety and outputs `True` if all content is grounded, or `False` if any ungrounded content is detected.
+Like 6 other AI-assisted evaluators, `GroundednessEvaluator` is a prompt-based evaluator that outputs a score on a 5-point scale (the higher the score, the more grounded the result is). On the other hand, `GroundednessProEvaluator` (preview) invokes our backend evaluation service powered by Azure AI Content Safety and outputs `True` if all content is grounded, or `False` if any ungrounded content is detected.
 
 We open-source the prompts of our quality evaluators except for `GroundednessProEvaluator` (powered by Azure AI Content Safety) for transparency. These prompts serve as instructions for a language model to perform their evaluation task, which requires a human-friendly definition of the metric and its associated scoring rubrics (what the 5 levels of quality mean for the metric). We highly recommend that users customize the definitions and grading rubrics to their scenario specifics. See details in [Custom Evaluators](#custom-evaluators).