I downloaded nltk data into the data directory in my Flask app. The views reside in a blueprint in another directory on the same level as the data directory. In the view I’m trying to set the path to the data, but it doesn’t work.
I want to check in a Python program if a word is in the English dictionary.
I reckoned that often the answer to my title is to go and read the documentations, but I ran through the NLTK book but it doesn’t give the answer. I’m kind of new to Python.
I am trying to process a user entered text by removing stopwords using nltk toolkit, but with stopword-removal the words like ‘and’, ‘or’, ‘not’ gets removed. I want these words to be present after stopword removal process as they are operators which are required for later processing text as query. I don’t know which are the words which can be operators in text query, and I also want to remove unnecessary words from my text.
I am currently looking for the way to replace words like first, second, third,…with appropriate ordinal number representation (1st, 2nd, 3rd).
I have been googling for the last week and I didn’t find any useful standard tool or any function from NLTK.
I am trying to run through a function with my million lines in a datasets.
I’m looking for a way to split a text into n-grams.
Normally I would do something like:
i would like a python library function that translates/converts across different parts of speech. sometimes it should output multiple words (e.g. “coder” and “code” are both nouns from the verb “to code”, one’s the subject the other’s the object)
I wanted to use wordnet lemmatizer in python and I have learnt that the default pos tag is NOUN and that it does not output the correct lemma for a verb, unless the pos tag is explicitly specified as VERB.