BERT's Conceptual Cartography: Mapping the Landscapes of Meaning
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Characterizing Linguistic Shifts in Croatian News via Diachronic Word Embeddings
A Comparative Analysis of Static Word Embeddings for Hungarian
Geological Inference from Textual Data using Word Embeddings
Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work
Comply: Learning Sentences with Complex Weights inspired by Fruit Fly Olfaction
QuanTaxo: A Quantum Approach to Self-Supervised Taxonomy Expansion
토론
이 논문과 연결된 포럼 글이 아직 없습니다.