Datasets:

toloka
/

TolokerGraph

Tasks:

Graph Machine Learning

Size:

Tags:

License:

Dataset card Viewer Files Files and versions Community

Dataset Preview

Full Screen Viewer

Full Screen

Split (1)

train

The full dataset viewer is not available (click to read why). Only showing a preview of the rows.

The dataset generation failed because of a cast error

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'target', 'source'}) and 9 missing columns ({'english_profile', 'approved_rate', 'expired_rate', 'skipped_rate', 'rejected_rate', 'education', 'banned', 'id', 'english_tested'}).

This happened while the csv dataset builder was generating data using

hf://datasets/toloka/TolokerGraph/edges.tsv (at revision f40575420823ccfbc55dce92e82d506b041c4abf)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              source: int64
              target: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 481
              to
              {'id': Value(dtype='int32', id=None), 'approved_rate': Value(dtype='float32', id=None), 'skipped_rate': Value(dtype='float32', id=None), 'expired_rate': Value(dtype='float32', id=None), 'rejected_rate': Value(dtype='float32', id=None), 'education': Value(dtype='string', id=None), 'english_profile': Value(dtype='bool', id=None), 'english_tested': Value(dtype='bool', id=None), 'banned': Value(dtype='bool', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'target', 'source'}) and 9 missing columns ({'english_profile', 'approved_rate', 'expired_rate', 'skipped_rate', 'rejected_rate', 'education', 'banned', 'id', 'english_tested'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/toloka/TolokerGraph/edges.tsv (at revision f40575420823ccfbc55dce92e82d506b041c4abf)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

id int32	approved_rate float32	skipped_rate float32	expired_rate float32	rejected_rate float32	education string	english_profile bool	english_tested bool	banned bool
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null

End of preview.

Toloker Graph: Interaction of Crowd Annotators

Dataset Summary

This repository contains a graph representing interactions between crowd annotators on a project labeled on the Toloka crowdsourcing platform (see the Toloka overview for the details on the used terminology).

The graph contains 11,758 nodes and 519,000 edges. Each node represents an individual annotator; nodes are provided with four numerical and three categorical features. An edge is drawn between a pair of annotators if they annotated the same task. Also, each node is provided with a label showing whether the annotator was banned on this project, or not.

Nodes

Nodes are stored in the nodes.tsv file in the TSV format of the following structure:

id: unique identifier of the annotator
approved_rate: percentage of the approved labels of this annotator
skipped_rate: percentage of the skipped tasks of this annotator
expired_rate: percentage of the expired tasks of this annotator
rejected_rate: percentage of the rejected labels of this annotator
education: level of education as self-reported by this annotator (none, basic, middle, high)
english_profile: knowledge of English as self-reported by this annotator (0 for no, 1 for yes)
english_tested: whether the annotator passed the Toloka language test for English (0 for no, 1 for yes)
banned: whether the annotator was banned on this project (0 for no, 1 for yes)

The *_rate attributes should sum up to 1.

Edges

Edges are stored in the edges.tsv file in the TSV format of the following structure:

source: source identifier of the annotator
target: target identifier of the annotator

As the graph is undirected, source and target can be interchanged for the given pair of nodes.

Citation

Likhobaba, D., Pavlichenko, N., Ustalov, D. (2023). Toloker Graph: Interaction of Crowd Annotators. Zenodo. https://doi.org/10.5281/zenodo.7620795

@dataset{Tolokers,
  author     = {Likhobaba, Daniil and Pavlichenko, Nikita and Ustalov, Dmitry},
  title      = {{Toloker Graph: Interaction of Crowd Annotators}},
  year       = {2023},
  publisher  = {Zenodo},
  doi        = {10.5281/zenodo.7620795},
  url        = {https://github.com/Toloka/TolokerGraph},
  language   = {english},
}

Copyright

Licensed under the Creative Commons Attribution 4.0 License. See LICENSE file for more details.

Downloads last month: 48

Edit dataset card