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README.md
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#
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## Acknowledgement
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Authors:
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dr. Izidor Mlakar, Rigon Sallauka, dr. Umut Arioz, dr. Matej Rojc
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## Data Integration and Preprocessing
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We begin by merging two distinct datasets of English medical texts. This step ensures a robust and diverse corpus, combining the strengths of both datasets. Following the integration, we preprocess the texts to clean the data, which includes removal of strings that do not contain relevant information. This preprocessing step is crucial to ensure the texts are in an optimal format for subsequent annotation.
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- `Human:`
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- `Assistant:`
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- Hyphens between words (`-`) were replaced with a single space.
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size_categories:
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# Italian NER dataset
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## Acknowledgement
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Authors:
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dr. Izidor Mlakar, Rigon Sallauka, dr. Umut Arioz, dr. Matej Rojc
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## Dataset Building
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## Data Integration and Preprocessing
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We begin by merging two distinct datasets of English medical texts. This step ensures a robust and diverse corpus, combining the strengths of both datasets. Following the integration, we preprocess the texts to clean the data, which includes removal of strings that do not contain relevant information. This preprocessing step is crucial to ensure the texts are in an optimal format for subsequent annotation.
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- `Human:`
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- `Assistant:`
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- `\n` (newline characters)
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- `\t` (tab characters)
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- Hyphens between words (`-`) were replaced with a single space.
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