updated landing page text

docs/index.rst

@@ -12,21 +12,22 @@
 Welcome to :code:`folktexts`' documentation!
 ============================================
 
-The :code:`folktexts` package enables you to benchmark and evaluate LLMs as risk
-scores.
+The :code:`folktexts` package enables you to benchmark and evaluate 
+LLM-generated risk scores.
 
-We encode unrealizable tabular prediction tasks as natural-language text,
-and prompt LLMs for the probability of target variable being true.
+We encode unrealizable tabular prediction tasks as natural language text tasks,
+and prompt LLMs for the probability of a target variable being true.
 The correct solutions for each task often require expressing uncertainty, as the
 target variable is not uniquely determined by the input features.
 
-Folktexts is compatible with any huggingface transformer model.
+Folktexts is compatible with any huggingface transformer model and models 
+available through web APIs (e.g., OpenAI API).
 
 Five tabular data tasks are provided out-of-the-box, using the American
 Community Survey as a data source: `ACSIncome`, `ACSMobility`, `ACSTravelTime`, 
-`ACSEmployment`, and `ACSPublicCoverage`. These tasks follow the same name, feature 
-columns, and target columns as those put forth by `Ding et al. (2021)`_ in the
-`folktables`_ python package.
+`ACSEmployment`, and `ACSPublicCoverage`. These tasks follow the same name, 
+feature columns, and target columns as those put forth by `Ding et al. (2021)`_ 
+in the `folktables`_ python package.
 
 
 Full code available on the `GitHub repository`_,