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README.md
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The ERWT series were trained for evaluation purposes, and therefore carry some critical limitations.
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###
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Many of the limitations are a direct result of the data. ERWT models are trained on a rather small subsample of nineteenth-century British newspapers, and its predictions have to be understood in this context (remember, Her Majesty?). Moreover, the corpus has a strong Metropolitan and liberal bias (see section on Data Description for more information).
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Want to know how much, then read our paper!
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##
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The ERWT models are trained on an openly accessible newspaper corpus created by the [Heritage Made Digital (HMD) newspaper digitisation project](footnote{https://blogs.bl.uk/thenewsroom/2019/01/heritage-made-digital-the-newspapers.html).
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The HMD newspapers comprise around 2 billion words in total, but the bulk of the articles originate from the (then) liberal paper *The Sun*.
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The ERWT series were trained for evaluation purposes, and therefore carry some critical limitations.
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### Training Data
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Many of the limitations are a direct result of the data. ERWT models are trained on a rather small subsample of nineteenth-century British newspapers, and its predictions have to be understood in this context (remember, Her Majesty?). Moreover, the corpus has a strong Metropolitan and liberal bias (see section on Data Description for more information).
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Want to know how much, then read our paper!
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## Data Description
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The ERWT models are trained on an openly accessible newspaper corpus created by the [Heritage Made Digital (HMD) newspaper digitisation project](footnote{https://blogs.bl.uk/thenewsroom/2019/01/heritage-made-digital-the-newspapers.html).
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The HMD newspapers comprise around 2 billion words in total, but the bulk of the articles originate from the (then) liberal paper *The Sun*.
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