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1. RuTaBERT RuTaBERTPublic

   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 PageRPublic

   Python 7

3. CoLeM CoLeMPublic

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

   Python 4

4. LoReTA LoReTAPublic

   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 PDFparsPublic

   Java 2

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

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

   Jupyter Notebook 2 1