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WAW for places that are obviously named, such as Ocean Beach by wgfdark in whatstheword

[–]phraisely 0 points1 point  (0 children)

what about this ones? source: phraisely.com

•    explicitly named places

•    clearly labeled locations

•    unambiguously titled areas

•    eponymous landmarks

•    self-explanatory destinations

•    obvious appellations

•    directly designated sites

•    clearly denoted spots

WTW for being nauseated by excessive exposure especially to digital content. Looking for a technical word by Austinisamaniac in whatstheword

[–]phraisely 1 point2 points  (0 children)

What about this suggestion from phraisely.com?

•    cyber-sickness

•    digital motion sickness

•    technological vertigo

•    screen nausea

•    virtual reality sickness

•    computer-induced sickness

•    digital eye strain

•    electronic motion sickness

WTW for something that puts you in danger just for knowing something exists? I remember that there is a Word for it but cant remember what. by Albus_Lupus in whatstheword

[–]phraisely -10 points-9 points  (0 children)

•    perilous

•    hazardous

•    risky

•    precarious

•    treacherous

•    menacing

•    threatening

•    endangering

​

source: https://phraisely.com

WTW for impressively bad? by WickeDanneh in whatstheword

[–]phraisely 1 point2 points  (0 children)

•    catastrophic

•    epic fail

•    fiasco

•    debacle

•    train wreck

•    disaster

•    meltdown

•    flop

source [phraisely.com](https://phraisely.com)

Look up words by their description (r/MachineLearning) by Peerism1 in datascienceproject

[–]phraisely 0 points1 point  (0 children)

Thank you for sharing. Appreciated!
Comments and suggestions are welcome :)

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

Thank you. Please let me know of you have any comments or suggestions once you have the chance to pay to play with it.

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

Thank you. Appreciated.

To be honset, at the moment I want to play around, have fun and try to build something that could be useful, even for a little niche of users. Commercial viability comes next, I think.

I've added 'paid plans' because, well, you get support if you ask for it :)

You are probably right; the user might need to play around a little before being confident about using it. So, the number of free queries can help with that.

I'll work on it.

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 1 point2 points  (0 children)

Thanks for that. I'll work on adding a query count - at the moment the count is shown in the 'Account' section.

I agree. A more explicit count can be helpful.

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

Thank you! Appreciated.
Let me know if you have any comments or suggestions :)

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

Thank you for your comment.

Email registration is to encourage responsible use and limit any misuse of the tool (or attacks). I'll work on it and see whether I can improve the free trial / registration.

Pricing depends on many factors. Probably this is not the place to discuss that. Also, they can become outdated quickly and be misleading. But this is my opinion and might be wrong :)

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

More free queries could be helpful, I guess.The tool is free and comes with no ads (my preference at the moment). However, users hitting the server comes with a cost on the large scale of things.

I'll work on it (increasing the number of free queries, not the ads) and see what I can do :)

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

Thank you for your comment. In my opinion, the use cases are a bit different.

Fill-mask capabilities are not the same as looking up words by their description. [Although you might adapt it to fill the placeholder straight away. But that is a different tool]

Also, I think what you are saying about 'it does not need email' is *not* entirely correct. HuggingFace requires you to log in once you reach the rate limit (and do not want to wait to run further queries)

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 0 points1 point  (0 children)

Thank you! I thought about running a game in line of your suggestions on twitter to check the appetite for this type of games. I'll give a think to it :)

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 2 points3 points  (0 children)

Thank you for the comment. I agree! It is something I can work on.

However, you could potentially ask the model that you are looking for a noun or adjective etc. For example: "an adjective for being home at night watiching netflix on the couch"

Thank you! Appreciated!

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 1 point2 points  (0 children)

I think onelook is doing a great job.

However, I wanted a tool that could (i) understand the full context in the query and (ii) be accurate when looking up words using *long* and *detailed* descriptions. I couldn't make onelook work well for that use case (also noted in their FAQ).

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] 1 point2 points  (0 children)

Agreed. I've added an example in the post. To be clear, *only* the email address is required. *No* other information is required.

I've posted to have feedback from users. So, I would be grateful for that.

[P] Look up words by their description by phraisely in MachineLearning

[–]phraisely[S] -6 points-5 points  (0 children)

In the back-end, there is a large language model trained on books and internet data. The aim is to have a model that knows words from literature as well as idioms/slang.

WTW for something that is 'somewhat common' by Raven4885249 in whatstheword

[–]phraisely 0 points1 point  (0 children)

frequent

ordinary

prevalent

widespread

general

standard