The world of pronouns is changing. From a closed class of words with few
members to a much more open set of terms to reflect identities. However,
Natural Language Processing (NLP) is barely reflecting this linguistic shift,
even though recent work outlined the harms of gender-exclusive language
technology. Particularly problematic is the current modeling 3rd person
pronouns, as it largely ignores various phenomena like neopronouns, i.e.,
pronoun sets that are novel and not (yet) widely established. This omission
contributes to the discrimination of marginalized and underrepresented groups,
e.g., non-binary individuals. However, other identity-expression phenomena
beyond gender are also ignored by current NLP technology. In this paper, we
provide an overview of 3rd person pronoun issues for NLP. Based on our
observations and ethical considerations, we define a series of desiderata for
modeling pronouns in language technology. We evaluate existing and novel
modeling approaches w.r.t. these desiderata qualitatively, and quantify the
impact of a more discrimination-free approach on established benchmark data.

本文探讨了 NLP 在第三人称代词领域的问题及其对边缘化群体的歧视和影响，提出了对代词建模的伦理准则，并基于此评估了现有和新颖的建模方法，量化了更不具歧视性的方法对基准数据的影响。