Papers by Nikola Obreshkov

1 papers
Natural Language Processing Pipeline to Annotate Bulgarian Legislative Documents (2020.lrec-1)

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Challenge: The Bulgarian MARCELL corpus consists of 25,283 documents, which are classified into eleven types.
Approach: They present the Bulgarian MARCELL corpus, part of a newly developed multilingual corpus representing the national legislation in seven European countries.
Outcome: The proposed corpus represents the national legislation in seven European countries and the NLP pipeline that turns the web crawled data into structured, linguistically annotated dataset.

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