WordReference VS WordNet

I rely on wordreference.com as a dictionary. It is very extensive and the forum is a goldmine. Source: 11 months ago

I recommend using wordreference.com. It will give you a bunch of alternate uses so you can try to sus out the pragmatics from context more effectively. This is especially useful for words like venir. Source: 12 months ago

Look up words in a dictionary and use a grammar book to help. If you don't have a dictionary and can't get hold of one, http://wordreference.com is a good resource. Source: almost 1 year ago

"trans" (the prefix) means "across"/"beyond"/"the other side of", so I would assume trans-gender would mean a different gender (in pretty much any language), not "someone with gender dysphoria" Transgender in french is "transgenre" with genre meaning "gender" and trans, most likely, meaning the same in english and french. Also, on wordreference.com it says transgenre means "(person) with different gender... Source: about 1 year ago

You're doing nothing wrong, it's that no app is perfect! I use wordreference.com , it is the most accurate online dictionary, and even though it might not be exactly what you're looking for, forvo.com is also a great tool for pronunciation. For verb conjugations, some learners use cooljugator.com but I find it has many mistakes, so, not ideal. You could try instead... Source: about 1 year ago

TL;DR: The authors pretrain the model to classify images into Wordnet synsets[a] that appear in the caption, using a standard Cross Entropy loss. They keep the number of classes relatively small by removing any synsets that don't show up in captions at least 500 times in the dataset. It seems to work well. My immediate question is: Why not classify among the entire hierarchy of all Wordnet synsets? --- [a]... - Source: Hacker News / 8 days ago

To operationalize this intuition, the Microsoft and UC Berkeley researchers use WordNet and Wiktionary to augment the text in image-text pairs. The concept itself is augmented for isolated concepts, such as the class labels in ImageNet, whereas for captions (such as from GCC), the least common noun phrase is augmented. Equipped with this additional structured knowledge, contrastively pretrained models exhibit... - Source: dev.to / about 2 months ago

If you like this, definitely check out WordNet (https://wordnet.princeton.edu/). - Source: Hacker News / 4 months ago

I didn't understand well what you meant, but maybe this site can help you: https://wordnet.princeton.edu/. Source: about 1 year ago

What I'd do is work with a huge database like WordNet and then try to "extrapolate" BIP39 to 4096 words by creating queries against WordNet to obtain words meeting the constraints you'd like to keep. Source: over 1 year ago