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Étiqueté : corpus linguistics

The image presents a visual metaphor for the evolving relationship between Generative AI and Corpus Linguistics, using a sleek, biomechanical version of the Ouroboros (a serpent consuming its own tail).Formed into an infinity loop ($\infty$), the serpent is rendered in brushed gold-tone scales with cyan circuit-line accents, signifying the fusion of ancient cycles with modern technology. The left loop of the infinity symbol houses floating holographic interfaces of leading AI entities, including OpenAI, Gemini, Hugging Face, and Copilot. The right loop contains the traditional foundations of linguistic study: Sketch Engine, the British National Corpus (BNC), and the International Corpus of English (ICE).The composition illustrates the "data loop" or "model collapse" theory: the process where AI models are trained on human-generated corpora, only to eventually consume and produce data that feeds back into the global digital ecosystem. 1

Corpus linguistics in the LLM era – the changing nature of language data

The emergence of Large Language Models (LLMs) has brought both opportunities and challenges to the field of corpus linguistics. These AI systems generate vast amounts of language output that often appear natural, but is this output genuinely authentic? This raises important questions for corpus linguists about the nature of linguistic data and the methods used to study it.

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Manipulate data with dplyr

The dplyr package is based on a data manipulation ‘grammar’. This grammar provides a consistent set of ‘verbs’ that solve the most common data manipulation tasks. I illustrate five of these ‘verbs’: filter(), arrange(), select(), mutate(), and summarise().