[DOC] minor changes

docs/Intro/Basics.rst

@@ -22,7 +22,7 @@ AI: data, models, and knowledge. Below is an overview of the ABL-Package.
 
 **Data** part manages the storage, operation, and evaluation of data efficiently.
 It includes the ``ListData`` class, which defines the data structures used in
-Abductive Learning, and comprises common data operations like insertion, deletion, 
+ABL, and comprises common data operations like insertion, deletion, 
 retrieval, slicing, etc. Additionally, it contains a series of evaluation metrics 
 such as ``SymbolAccuracy`` and ``ReasoningMetric`` (both specialized metrics 
 inherited from the ``BaseMetric`` class), for evaluating model quality from a 

docs/Intro/Learning.rst

@@ -15,7 +15,7 @@ In this section, we will look at how to build the learning part.
 In ABL-Package, building the learning part involves two steps:
 
 1. Build a machine learning base model used to make predictions on instance-level data.
-2. Instantiate an ``ABLModel`` with the base model, which enables the learning part to train, test, and predict on example-level data.
+2. Instantiate an ``ABLModel`` with the base model, which enables the learning part to process example-level data.
 
 .. code:: python