Computational Corpus Ling

3 Credits · Level: Graduate, Undergraduate

Digital linguistic corpora, i.e. electronic collections of written, spoken or multimodal language data, have become an increasingly important source of empirical information for computational, theoretical and applied linguistics in recent years, as well as underpinning much work in Artificial Intelligence and instruction fine-tuning for Large Language Models. This course is meant as a theoretically founded, practical introduction to corpus work with a broad selection of data, including non-standardized varieties such as language on the Internet, learner corpora and spoken corpora. We will discuss issues of corpus design, annotation and evaluation using quantitative methods and both manual and automatic annotation tools for different levels of linguistic analysis, from parts-of-speech and lexicography, through aspects of syntax, semantics and discourse annotation. As part of the course, students will participate in the creation of a multilayer corpus that will be built up as the course progresses.