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textacy v0.3.3 Release Notes

Release Date: 2017-02-10 // about 7 years ago

  • 🆕 New and Changed:

    • ➕ Added a consistent normalize param to functions and methods that require token/span text normalization. Typically, it takes one of the following values: 'lemma' to lemmatize tokens, 'lower' to lowercase tokens, False-y to not normalize tokens, or a function that converts a spacy token or span into a string, in whatever way the user prefers (e.g. spacy_utils.normalized_str()).
      • Functions modified to use this param: Doc.to_bag_of_terms(), Doc.to_bag_of_words(), Doc.to_terms_list(), Doc.to_semantic_network(), Corpus.word_freqs(), Corpus.word_doc_freqs(), keyterms.sgrank(), keyterms.textrank(), keyterms.singlerank(), keyterms.key_terms_from_semantic_network(), network.terms_to_semantic_network(), network.sents_to_semantic_network()
    • 👉 Tweaked keyterms.sgrank() for higher quality results and improved internal performance.
    • When getting both n-grams and named entities with Doc.to_terms_list(), filtering out numeric spans for only one is automatically extended to the other. This prevents unexpected behavior, such as passing filter_nums=True but getting numeric named entities back in the terms list.

    🛠 Fixed:

    • keyterms.sgrank() no longer crashes if a term is missing from idfs mapping. (@jeremybmerrill, issue #53)
    • Proper nouns are no longer excluded from consideration as keyterms in keyterms.sgrank() and keyterms.textrank(). (@jeremybmerrill, issue #53)
    • Empty strings are now excluded from consideration as keyterms — a bug inherited from spaCy. (@mlehl88, issue #58)