update file names

Author: laujan

articles/ai-services/translator/text-translation/reference/v4/reference-overview.md

@@ -85,12 +85,12 @@ The following tables list available metrics with description of how they're used
 | Metrics | Description |
 |:----|:-----|
 |`ActiveTokens`|Total tokens minus cached tokens over a period of time. Applies to `PTU` and `PTU`-managed deployments. Use this metric to understand your `TPS`- or `TPM`-based utilization for `PTU`s and compare your benchmarks for target `TPS` or `TPM` for your scenarios. <br> To breakdown API requests, you can add a filter or apply splitting by the following dimensions: `ModelDeploymentName`, `ModelName`, `ModelVersion`.|
-|`GeneratedTokens`|Number of tokens generated (output) from an OpenAI model. Applies to `PTU`, `PTU`-managed, and Pay-as-you-go deployments. To break down this metric, you can add a filter or apply splitting by the following dimensions:<br>`ModelDeploymentName`or `ModelName`.|
+|`GeneratedTokens`|Number of tokens generated (output) from an OpenAI model. Applies to `PTU`, `PTU`-managed, and Pay-as-you-go deployments. To analyze this metric in detail, you can add a filter or apply splitting by the following dimensions:<br>`ModelDeploymentName`or `ModelName`.|
 |`FineTunedTrainingHours`|Number of training hours processed on an OpenAI fine-tuned model.|
-|`TokenTransaction`|Number of inference tokens processed on an OpenAI model. Calculated as prompt tokens (input) plus generated tokens (output). Applies to `PTU`, `PTU`-managed, and Pay-as-you-go deployments. To break down this metric, you can add a filter or apply splitting by the following dimensions:<br>`ModelDeploymentName`or `ModelName`.|
-|`ProcessedPromptTokens`|Number of prompt tokens processed (input) on an OpenAI model. Applies to `PTU`, `PTU`-managed, and Pay-as-you-go deployments. To break down this metric, you can add a filter or apply splitting by the following dimensions:<br>`ModelDeploymentName`or `ModelName`.|
+|`TokenTransaction`|Number of inference tokens processed on an OpenAI model. Calculated as prompt tokens (input) plus generated tokens (output). Applies to `PTU`, `PTU`-managed, and Pay-as-you-go deployments. To analyze this metric in detail, you can add a filter or apply splitting by the following dimensions:<br>`ModelDeploymentName`or `ModelName`.|
+|`ProcessedPromptTokens`|Number of prompt tokens processed (input) on an OpenAI model. Applies to `PTU`, `PTU`-managed, and Pay-as-you-go deployments. To analyze this metric in detail, you can add a filter or apply splitting by the following dimensions:<br>`ModelDeploymentName`or `ModelName`.|
 |`AzureOpenAIContextTokensCacheMatchRate`|Percentage of prompt tokens that hit the cache. Applies to `PTU` and `PTU`-managed deployments.
-|`AzureOpenAIProvisionedManagedUtilizationV2`|Utilization percentage for a provisioned-managed deployment, calculated as (`PTU`s consumed / `PTU`s deployed) x 100. When utilization is greater than or equal to 100%, calls are throttled and error code 429 is returned. To break down this metric, you can add a filter or apply splitting by the following dimensions: `ModelDeploymentName`, `ModelName`, `ModelVersion`, and `StreamType` (streaming vs nonstreaming requests).|
+|`AzureOpenAIProvisionedManagedUtilizationV2`|Utilization percentage for a provisioned-managed deployment, calculated as (`PTU`s consumed / `PTU`s deployed) x 100. When utilization is greater than or equal to 100%, calls are throttled and error code 429 is returned. To analyze this metric in detail, you can add a filter or apply splitting by the following dimensions: `ModelDeploymentName`, `ModelName`, `ModelVersion`, and `StreamType` (streaming vs nonstreaming requests).|