In this article we present the Frankfurt Latin Lexicon (FLL), a lexical resource for Medieval Latin that is used both for the lemmatization of Latin texts and for the post-editing of lemmatizations.
We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages.
In this paper, we present the first publicly available part-of-speech and morphologically tagged corpus for the Albanian language, as well as a neural morphological tagger and lemmatizer trained on it.
We present a system description of our contribution to the CoNLL 2019 shared task, Cross-Framework Meaning Representation Parsing (MRP 2019).
In this study, we present Morpheus, a joint contextual lemmatizer and morphological tagger.
This paper studies the use of NMT (neural machine translation) as a normalization method for an early English letter corpus.
English verbs have multiple forms.
Lemmatization of standard languages is concerned with (i) abstracting over morphological differences and (ii) resolving token-lemma ambiguities of inflected words in order to map them to a dictionary headword.