Normalization is a process used in database design to eliminate redundancy and improve data integrity. It involves breaking down a database into smaller, more manageable tables and establishing relationships between them. The process of normalization is not automatic, and it requires a deep understanding of the dependency between attributes.

Dependency between Attributes
Normalization is based on the concept of functional dependency, which refers to the relationship between two attributes in a database table. Functional dependency occurs when the value of one attribute determines the value of another attribute. For example, in a table of student records, the attribute "student ID" determines the attributes "name" and "address".

First Normal Form (1NF)
The first step in the normalization process is to ensure that each table satisfies the first normal form (1NF). This means that each attribute in a table must be atomic, meaning it cannot be further divided. Additionally, each attribute must have a unique name, and the order of the rows and columns should not matter.

Second Normal Form (2NF)
The second normal form (2NF) is achieved by eliminating partial dependencies. A partial dependency occurs when an attribute depends on only a part of the primary key. To eliminate partial dependencies, tables are split into separate tables, each with a unique primary key.

Third Normal Form (3NF)
The third normal form (3NF) eliminates transitive dependencies. A transitive dependency occurs when an attribute depends on another attribute that is not part of the primary key. To achieve 3NF, tables are further split, and attributes that depend on each other are placed in separate tables.

Other Normal Forms
There are higher normal forms such as Boyce-Codd Normal Form (BCNF) and Fourth Normal Form (4NF) that deal with more specific types of dependencies and can be applied if necessary.

Manual Process with Semantic Information
Normalization is a manual process that requires careful analysis of the data and an understanding of the relationships between attributes. It involves identifying functional dependencies, determining the appropriate primary key, and breaking down tables to eliminate redundancy and improve data integrity. Semantic information, such as the meaning and context of the data, is essential in this process to ensure that the database accurately represents the real-world entities and their relationships.

In conclusion, the process of normalization is not automatic and requires an understanding of dependency between attributes. It involves breaking down tables, establishing relationships, and eliminating redundancy to improve data integrity. Semantic information plays a crucial role in ensuring the accuracy and effectiveness of the normalization process.