Addresses some typos in the README.

Author: nrfulton

README.md

@@ -99,7 +99,7 @@ pre-commit install
 
 Mellea supports validation of generation results through a **instruct-validate-repair** pattern.
 Below, the request for *"Write an email.."* is constrained by the requirements of *"be formal"* and *"Use 'Dear interns' as greeting."*.
-Using a simple rejection sampling strategy, the request is send up to three (loop_budget) times to the model and
+Using a simple rejection sampling strategy, the request is sent up to three (loop_budget) times to the model and
 the output is checked against the constraints using (in this case) LLM-as-a-judge.
 
 
@@ -133,11 +133,11 @@ print(f"***** email ****\n{str(email_v1)}\n*******")
 
 ## Getting Started with Generative Slots
 
-Generative slots allow to define functions without implementing them.
-By using the `@generative` decorator, the function gets converted into an LLM function.
-The example below, is a minimal version of writing a sentiment classification function
-using Mellea's generative slots and a local LLM.
-
+Generative slots allow you to define functions without implementing them.
+The `@generative` decorator marks a function as one that should be interpreted by querying an LLM.
+The example below demonstrates how an LLM's sentiment classification
+capability can be wrapped up as a function using Mellea's generative slots and
+a local LLM.
 
 
 ```python