Okay, so today I wanna share my experience messing around with something I called “luke hulk”. Yeah, kinda cheesy name, I know, but it stuck. Basically, I was trying to build a system that could take some text input and then generate some cool visual representations of the key concepts within it. Think like, mind-mapping on steroids, but way simpler and probably a lot dumber.
It all started when I stumbled across some open-source NLP libraries. I’d always been vaguely interested in how computers understand language, but never really dove in. So, I grabbed a few, the usual suspects, and started playing around. First thing I did was just trying to get it to identify the main entities in a piece of text. Like, if I fed it “Luke Skywalker fought Darth Vader,” it would spit out “Luke Skywalker” and “Darth Vader” as the important bits.
That part was actually surprisingly easy. The libraries did most of the heavy lifting. I just had to write a little Python code to glue it all together. Then came the fun part – visualizing it. I initially thought about doing some crazy 3D graph thing, but quickly realized that was way beyond my skill level. So, I scaled it back. Way back.
I decided to just generate a simple network graph. Each entity would be a node, and the connections between them would represent how often they appeared together in the text. I used a library called NetworkX for this. I’d never used it before, but the documentation was pretty good, and I managed to get something working after a few hours of banging my head against the keyboard.
The initial results were… underwhelming. Just a bunch of circles and lines. Hard to read, not particularly insightful. But then I started tweaking things. I changed the size of the nodes based on their “importance” (i.e., how many times they appeared in the text). I made the connections thicker if the entities were closely related. I added some color-coding. Slowly but surely, it started to look a bit more interesting.
I even tried adding sentiment analysis into the mix. So, if two entities were mentioned together in a positive context, the line connecting them would be green. If it was negative, the line would be red. That was kinda cool, but also kinda messy. It worked well on simple examples, but got confused easily with more complex sentences.
The whole thing is still pretty rough around the edges. It’s definitely not ready for prime time. But it was a fun little project, and I learned a ton about NLP and graph visualization. Plus, it gives me a good starting point for future experiments. Maybe one day I’ll actually be able to build that mind-mapping-on-steroids thing I originally envisioned. Or maybe I’ll just stick to generating slightly less-terrible network graphs. Who knows?
If you’re thinking about dabbling in this kind of stuff yourself, I’d say go for it. Don’t be afraid to start small and experiment. There are tons of great open-source tools out there, and the possibilities are endless. Just be prepared to spend a lot of time debugging and tweaking. And maybe come up with a better name than “luke hulk.” Seriously, I’m still embarrassed about that one.
Anyway, that’s my “luke hulk” story. Hope you found it somewhat interesting, or at least mildly amusing. Cheers!
