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1. RuTaBERT RuTaBERT Public

   RuTaBERT is a framework for solving column type and property annotation problems based on fine-tuning a pre-trained language model (e.g., BERT) using a large-scale corpus of Russian-language tables.

   Python 7 1

2. PageR PageR Public

   Python 7

3. CoLeM CoLeM Public

   CoLeM framework is a table model based on contrastive learning techniques for solving the problem of Column Type Annotation.

   Python 4

4. LoReTA LoReTA Public

   Dataset from the authors of RuTaBERT and is based on the Russian Web Tables. Only relational tables were chosen from Russian Web Tables with headers matching their selected 170 DBpedia semantic types.

   Jupyter Notebook 2 1

5. PDFpars PDFpars Public

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6. ru-facts-200 ru-facts-200 Public

   Russian-Facts-200 (RF-200): A novel benchmark for fact extraction from Russian tabular data.

   Jupyter Notebook 2 1