What is the role of the window width when machine-learning part-of-speech tags?
the size of the context that is kept around the word that is to be tagged. for example, with a window width of 5, the two words before and after are added as input to the learning system
Explain the role of word embeddings when learning part-of-speech tags, and the idea behind tfidf
a word embedding maps a word to a vector of numbers that can be used as input to a neural network. tfidf is a specific embedding, whose definition uses the frequency of words in the documents of the corpus to map words to numbers.
Briefly explain what part-of-speech tagging means
The process of attributing to every word in a corpus its syntactic category, like noin, participle etc.
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