It appears that we are currently experiencing a connectivity issue that is preventing us from directly accessing and reading the files at this moment. Nevertheless, I am more than capable of guiding you through a systematic approach to check for duplicate content within the datasets you have.

Here’s a detailed approach you can take to effectively identify duplicates:

1. **Loading the files**: Begin by reading each file into a separate variable or an appropriate data structure that suits the type of data you are working with. This could involve using libraries or functions that facilitate the reading of various file formats.

2. **Checking for duplicates**:
   - For text files, such as those with `.txt` or `.py` extensions, you can split the content into individual lines or words. This will allow you to systematically check for any duplicate entries within the text.
   - For CSV files, you can utilize a library like pandas to load the data into a DataFrame, which provides powerful tools for data manipulation. Alternatively, if you prefer a more manual approach, you can read the CSV files line by line to examine the contents.

3. **Identify duplicates**: Develop a mechanism to flag any duplicates that you discover during your checks. This could involve creating a list or a dictionary that not only records the duplicates but also includes their contexts, such as their line numbers or positions within the file.

4. **Format the issues**: Once you have identified the duplicates, use the provided format to create structured entries for each issue found. This will help in organizing the information clearly and make it easier to address the duplicates later on.

Since I am unable to access the files directly at this time, I encourage you to inspect the files on your local machine. By following these outlined steps, you should be able to effectively check for duplicates. Alternatively, if you would like to attempt uploading the files or providing the content here manually, I would be more than happy to assist you further. Would you like to proceed with that option?