BERT's Conceptual Cartography: Mapping the Landscapes of Meaning
This addresses the challenge for conceptual engineers in mapping word usage nuances, though it is incremental as it applies existing NLP methods to a new domain.
The paper tackled the problem of understanding the varied contextual usage of words for conceptual engineering by creating 2D conceptual landscapes using BERT and the British National Corpus, revealing that each word has a unique and intricate landscape, making a one-size-fits-all approach to improving words practically intractable at scale.
Conceptual Engineers want to make words better. However, they often underestimate how varied our usage of words is. In this paper, we take the first steps in exploring the contextual nuances of words by creating conceptual landscapes -- 2D surfaces representing the pragmatic usage of words -- that conceptual engineers can use to inform their projects. We use the spoken component of the British National Corpus and BERT to create contextualised word embeddings, and use Gaussian Mixture Models, a selection of metrics, and qualitative analysis to visualise and numerically represent lexical landscapes. Such an approach has not yet been used in the conceptual engineering literature and provides a detailed examination of how different words manifest in various contexts that is potentially useful to conceptual engineering projects. Our findings highlight the inherent complexity of conceptual engineering, revealing that each word exhibits a unique and intricate landscape. Conceptual Engineers cannot, therefore, use a one-size-fits-all approach when improving words -- a task that may be practically intractable at scale.