This paper reports the latest developments, planned works, and issues of the Corpas Náisiúnta na Gaeilge (henceforth: CNG, translation: the National Corpus of Irish) project, detailing the work that has been completed to date, current work, and planned future work. This report details the compilation of corpora, development of a project website and part-speech tagger, the challenges of expanding existing corpora, and the addition of historical and legal corpora. We also present the training and outreach activities of the project.

This paper introduces a taxonomy of phenomena which cause bias in machine translation, covering gender bias (people being male and/or female), number bias (singular you versus plural you) and formality bias (informal you versus formal you). Our taxonomy is a formalism for describing situations in machine translation when the source text leaves some of these properties unspecified (eg. does not say whether doctor is male or female) but the target language requires the property to be specified (eg. because it does not have a gender-neutral word for doctor). The formalism described here is used internally by a web-based tool we have built for detecting and correcting bias in the output of any machine translator.