Machine learning based on various forms of inductive inference has been used for a wide
range of problems in natural language processing, with syntactic parsing being one of the …

If machine learning models were to achieve superhuman abilities at various reasoning or
decision-making tasks, how would we go about evaluating such models, given that humans …

Annotated data is an essential ingredient in natural language processing for training and
evaluating machine learning models. It is therefore very desirable for the annotations to be …

Data quality is crucial for training accurate, unbiased, and trustworthy machine learning
models as well as for their correct evaluation. Recent works, however, have shown that even …

Learner corpora have generally focused on intermediate and advanced learners/users.
Corpora of beginners are rare but just as important. Second Language Acquisition (SLA) …

The co-existence of several treebanks for one language, made by different teams and
converted from different sources, within the Universal Dependencies (UD) platform (Nivre et …

In this paper we assess to what extent the available Portuguese treebanks and available
probabilistic parsers are suitable for out-of-the-box robust parsing of Portuguese. We also …

Dependency relations between words are increasingly recognized as an important level of
linguistic representation that is close to the data and at the same time to the semantic functor …

Cet article décrit l'effort d'amélioration de deux corpus du français annotés en dépendances
syntaxiques, qui s' inscrit dans le cadre du projet Universal Dependencies (UD) qui vise à …

Inconsistencies are part of any manually annotated corpus. Automatically finding these
inconsistencies and correcting them (even manually) can increase the quality of the data …