Categorizing Notes

A common problem in mechanical and medical data is associating notes with a category. In this challenge, you will automate the process of sorting mechanical notes into their correct category. Here’s an example:

INPUT

--List of Categories--

1. Scratch
2. Crack
3. Defect

--Notes--

1. The product was defective.
2. A crack was caused by client.
3. Many scratches noted.

OUTPUT

Note Category

1. The product was defective. Defect
2. A crack was caused by client. Crack
3. Many scratches noted. Scratch

Don't worry about using fancy machine learning or natural language processing models. This problem can be handled reasonably well using a total of 5 nodes (simple solution), and a more refined solution involves just 8 nodes (complex solution). Also don't worry about getting 100% accuracy.