Recent content by liam_thinker

For Natural Language Processing, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is getting started. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved...

I think step and automation is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. That should make it easier to tell whether the change is actually helping.

A useful way to understand Natural Language Processing is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is getting started. Define what a good result looks like before changing tools or settings, then test one variable at a time so...