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#wordnet — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #wordnet, aggregated by home.social.

  1. I had a lot of fun implementing a SPARQL editor for DanNet. During this process I also wrote a ton of new documentation, including a SPARQL tutorial that uses the new editor for its interactive examples.

    The idea is, of course, to make the Danish WordNet more broadly accessible. Previously, you would have had to spin up your own RDF triplestore to query DanNet using SPARQL.

    wordnet.dk/dannet/sparql

    #SPARQL #DanNet #WordNet

  2. Весь такой перцептивный. Сенсорная атмосфера в прозе. Пример анализа художественного текста на Python

    Анализ глаголов восприятия в прозе Паустовского с помощью Python: подход цифрового гуманитария для NLP-разработчиков.

    habr.com/ru/articles/977210/

    #проза #поэзия #писатель #python #pymorphy #tokenizer #spacy #wordnet

  3. This week's #Python topic is Natural Language Processing with #NLTK and #Wordnet.

    I studied language and IT seperately at uni a few decades ago. Wish I'd combined them.

    TIL there's a Wordnet for Scottish Gaelic. I'm excited about it but don't know what to do with it yet.

    Link to The Unified Scottish Gaelic Wordnet ukc.disi.unitn.it/index.php/ga

    #Gàidhlig #Gaelic

  4. It is a truth universally acknowledged, that an annotator in possession of a growing sign language wordnet must be in want of improved annotation support. We added shared-meaning auto-suggestions to our annotation interface, then we annotated 3 of our 8 languages some more. Find out more in our new paper, “Signs and Synonymity” #SignLanguage #SignLanguages #Wordnet
    sign-lang.uni-hamburg.de/lrec/

  5. I've been experimenting with using word clouds for illustrating collections of related synsets, e.g. the holonym substance relation for a specific synset (pictured: flour in Danish).

    It works quite well, but I did end up simulating the word sizes based entirely on the sort order of the weights, rather than deriving them more directly. I did this to get a fairly predictable appearance for clouds of any size.

    #wordcloud #tagcloud #wordnet #danish #visualisation #visualization

  6. Still slowly working on the #keyword extraction and storage in #json file.

    I didn't manage to enable #stopwords in #keyBERT, so the plan is to filter the keywords in additional step.

    The "#WordPress" or "plugin" keyword for each plugin would be useless.

    The next step that follows will be to find #synonyms for each keyword... and I think I'll be using NLTK #wordNet in #python. Not sure if it's the best option.

    12/:bongoCat:

  7. Still slowly working on the #keyword extraction and storage in #json file.

    I didn't manage to enable #stopwords in #keyBERT, so the plan is to filter the keywords in additional step.

    The "#WordPress" or "plugin" keyword for each plugin would be useless.

    The next step that follows will be to find #synonyms for each keyword... and I think I'll be using NLTK #wordNet in #python. Not sure if it's the best option.

    12/:bongoCat:

  8. Still slowly working on the #keyword extraction and storage in #json file.

    I didn't manage to enable #stopwords in #keyBERT, so the plan is to filter the keywords in additional step.

    The "#WordPress" or "plugin" keyword for each plugin would be useless.

    The next step that follows will be to find #synonyms for each keyword... and I think I'll be using NLTK #wordNet in #python. Not sure if it's the best option.

    12/:bongoCat:

  9. Still slowly working on the #keyword extraction and storage in #json file.

    I didn't manage to enable #stopwords in #keyBERT, so the plan is to filter the keywords in additional step.

    The "#WordPress" or "plugin" keyword for each plugin would be useless.

    The next step that follows will be to find #synonyms for each keyword... and I think I'll be using NLTK #wordNet in #python. Not sure if it's the best option.

    12/:bongoCat: