Unfortunately, with the current database that runs this site, I don't have data about which senses of ~term~ are used most commonly. I've got ideas about how to fix this but will need to find a source of "sense" frequencies. Hopefully there's enough info above to help you understand the part of speech of ~term~, and guess at its most common usage.
For those interested in a little info about this site: it's a side project that I developed while working on Describing Words and Related Words. Both of those projects are based around words, but have much grander goals. I had an idea for a website that simply explains the word types of the words that you search for – just like a dictionary, but focussed on the part of speech of the words. And since I already had a lot of the infrastructure in place from the other two sites, I figured it wouldn't be too much more work to get this up and running.
The dictionary is based on the amazing Wiktionary project by wikimedia. I initially started with WordNet, but then realised that it was missing many types of words/lemma (determiners, pronouns, abbreviations, and many more). This caused me to investigate the 1913 edition of Websters Dictionary – which is now in the public domain. However, after a day's work wrangling it into a database I realised that there were far too many errors (especially with the part-of-speech tagging) for it to be viable for Word Type.
Finally, I went back to Wiktionary – which I already knew about, but had been avoiding because it's not properly structured for parsing. That's when I stumbled across the UBY project – an amazing project which needs more recognition. The researchers have parsed the whole of Wiktionary and other sources, and compiled everything into a single unified resource. I simply extracted the Wiktionary entries and threw them into this interface! So it took a little more work than expected, but I'm happy I kept at it after the first couple of blunders.
Special thanks to the contributors of the open-source code that was used in this project: the UBY project (mentioned above), @mongodb and express.js.
Currently, this is based on a version of wiktionary which is a few years old. I plan to update it to a newer version soon and that update should bring in a bunch of new word senses for many words (or more accurately, lemma).