Update answer_relevance.md (#832)

Typo

Author: carllapierre

docs/concepts/metrics/answer_relevance.md

@@ -2,7 +2,7 @@
 
 The evaluation metric, Answer Relevancy, focuses on assessing how pertinent the generated answer is to the given prompt. A lower score is assigned to answers that are incomplete or contain redundant information and higher scores indicate better relevancy. This metric is computed using the `question`, the `context` and the `answer`. 
 
-The Answer Relevancy is defined as the mean cosine similartiy of the orginal `question` to a number of artifical questions, which where generated (reverse engineered) based on the `answer`: 
+The Answer Relevancy is defined as the mean cosine similartiy of the original `question` to a number of artifical questions, which where generated (reverse engineered) based on the `answer`: 
 
 ```{math}
 \text{answer relevancy} = \frac{1}{N} \sum_{i=1}^{N} cos(E_{g_i}, E_o)
@@ -66,4 +66,4 @@ To calculate the relevance of the answer to the given question, we follow two st
 
 - **Step 2:** Calculate the mean cosine similarity between the generated questions and the actual question.
 
-The underlying concept is that if the answer correctly addresses the question, it is highly probable that the original question can be reconstructed solely from the answer.
+The underlying concept is that if the answer correctly addresses the question, it is highly probable that the original question can be reconstructed solely from the answer.