wordnet

I know WordNet has Domains Hierarchy: e.g. sport->football. 1) Is it possible to list all words related, for example, to the 'sport->football' sub-domain? Response: goalkeeper, forward, penalty, ball, field, stadium, referee and so on. 2) Get domain's name for a given word , e.g. 'goalkeeper'? Need something like [sport->football; sport->hockey] or [football;hockey] or just 'football'. It is for a document classification task. WordNet has a hypernym / hyponym hierarchy but that is not what you want here, as you can see when you look up goalkeeper : from nltk.corpus import wordnet s = wordnet

i need to do function on arabic words by using python.. and i need to link arabic wordnet with python to do some method like : wn.synset('جميل') i find Multilingual Lexicons: AWN - ArabicWN http://www.talp.upc.edu/index.php/technology/resources/multilingual-lexicons-and-machine-translation-resources/multilingual-lexicons/72-awn and i try to run : A set of basic python functions for accessing the database http://nlp.lsi.upc.edu/awn/AWNDatabaseManagement.py.gz but when run the code(AWNDatabaseManagement.py) this error occur: processing file E:/usuaris/horacio/arabicWN/AWNdatabase/upc_db.xml file

I have a WordNet synset offset (for example id="n#05576222" ). Given this offset, how can I get the synset using Python? donners45 As of NLTK 3.2.3, there's a public method for doing this: wordnet.synset_from_pos_and_offset(pos, offset) In earlier versions you can use: wordnet._synset_from_pos_and_offset(pos, offset) This returns a synset based on it's POS and offest ID. I think this method is only available in NLTK 3.0 but I'm not sure. Example: from nltk.corpus import wordnet as wn wn._synset_from_pos_and_offset('n',4543158) >> Synset('wagon.n.01') For NTLK 3.2.3 or newer, please see

I am using the wordnet API from nltk. When I compare one synset with another I got None but when I compare them the other way around I get a float value. Shouldn't they give the same value? Is there an explanation or is this a bug of wordnet? Example: wn.synset('car.n.01').path_similarity(wn.synset('automobile.v.01')) # None wn.synset('automobile.v.01').path_similarity(wn.synset('car.n.01')) # 0.06666666666666667 alvas Technically without the dummy root, both car and automobile synsets would have no link to each other: >>> from nltk.corpus import wordnet as wn >>> x = wn.synset('car.n.01') >>>

I downloaded WN-Affect . I am however not sure how to use it to detect the mood of a sentence. For example if I have a string "I hate football." I want to be able to detect whether the mood is bad and the emotion is fear. WN-Affect has no tutorial on how to do it, and I am kind of new to python. Any help would be great! In short : Use SentiWordNet instead and look at https://github.com/kevincobain2000/sentiment_classifier In Long : Affectedness vs Sentiment The line between affect and sentiment is very fine. One should looking into Affectedness in linguistics studies, e.g. http://compling.hss