Titlebook: Building a National Corpus; A Welsh Language Cas Dawn Knight,Steve Morris,Mair Rees Book 2021 The Editor(s) (if applicable) and The Author(

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https://doi.org/10.1007/978-1-4939-2785-2ling these sub-corpora, and assesses the relative similarity (and differences) of the released corpus in comparison to its initial design (as presented in Chapter .). The chapter effectively presents the ‘results’ of our approach to building a corpus, by critically evaluating the final dataset. The

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https://doi.org/10.1007/978-3-030-81858-6corpus linguistics; minority languages; Welsh language; Welsh linguistics; CorCenCC; National corpora; e-l

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The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerl

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Understanding the Language Context, work on the CorCenCC project. This first chapter provides the context to the work and lays foundations for the first step of corpus building, that is, the examination of the context of the language. It begins with an exploration of what can be considered distinct about a ‘national’ corpus, and then

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(Meta)Data Collection,pter .), attention needs to be given to . will contribute data and . they will be recruited. This chapter focuses specifically on the stages of participant recruitment and (meta)data collection when building a corpus. Drawing on our experience in sourcing and collecting the (meta)data for CorCenCC,

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Processing and (Re)presenting Corpora,age data for future analysis. The chapter first details the importance of the transcription phase in spoken corpus development and documents how bespoke transcription conventions can be developed for, and employed in, a given target language. The tagging and collation of corpus data (via corpus mana

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Results, Reflections and Lessons Learnt,ling these sub-corpora, and assesses the relative similarity (and differences) of the released corpus in comparison to its initial design (as presented in Chapter .). The chapter effectively presents the ‘results’ of our approach to building a corpus, by critically evaluating the final dataset. The

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