Following on from the previous post, I realised that two of the headings – author and disclaimer are repetitive and so there is redundancy in the information in the database. So from the discussion, the process of removing the repetition is part of the process of normalisation of a database which in the most basic terms is about organising a database. This involves a bunch of other things but keeping it simple, removing the repetition is effective.
From the discussion, it looks as though an efficient way to remove the repetitive information is to store it as a separate table. So in this case, it would be author and disclaimer as separate tables. The posts are stored as a separate table and they have various fields. Then the disclaimer and author information remain as fields in the posts table but they are special fields in that they point to other tables for the information. This in turn results from the relationships in the database schema.
Thus there are keys that identify records and support relationships for instance between tables. Primary keys are found in the table and foreign keys are found in another table. So in the case of the author and disclaimer information, the database working through the posts table, would find a reference to a foreign key for disclaimer and would look in the disclaimer table.
I then requested for Chat GPT to update the table (saved as a text document) and it created the separate tables and denoted the relationship. This database is written as pseudocode but at this stage, it’s about understanding the principles. It looks as though it’s not too much of a leap for the pseudocode to be translated into SQL.
Previous Posts in the Series
Creating a Database for the Blog – Part 1
Notes on the Preparation of this Post
I was using Chat GPT 5.4 Thinking.
I’ve realised that just like research methodology, the post-writing preparation is quite technical and something as straightforward as the version of the LLM becomes an important part of the approach. So I might be able to relabel ‘Notes on the Preparation of this Post’ as ‘Methodology’ but I’ll have a think about it. It seems reasonable to suppose that different types of blogs would have different methodologies for the creation of posts.
Having generated the text database file, I can now feed this into the LLM as the starting point. I’ve just done a quick test by asking how many posts there are and the response was 3, so that’s a simple assurance although there is the history of the conversation so I may need to tighten up the prompting. I’m realising that the text database file and the processing of this by the LLM is a dyad that may benefit from an approach similar to the workflow for writing code. It’s also interesting to think about the parallels with diagnostic workup although they are obviously fundamentally different.
As in Part 1 in the series, this post has evolved from a ‘discussion’ with Chat GPT 5.4 Thinking.
I’ve boldened key database technical terms to highlight their presence as they are central to the undrestanding of the processes in this post.
I’m more mindful these days of trying to promote human artists where I can, so I’m including another artist from the Pexels collection.
Disclaimer
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