Sentencer from SpaCy and NLTK does not catch the fact that typical abbreviations (e.g.
Million in German) and the resulting sentence split is not correct. I understand that sentencers are supposed to be simple and quick but I am wondering if there is a better one that takes into account something more than uppercased words and punctuation? Alternatively, how to make SpaCy / NLTK / ... sentencer work for such sentences?
I am interested primarily with sentencers with Python API.