metadata

annotations_creators:
  - synthetic
language_creators:
  - other
language:
  - python
license:
  - Apache 2.0 Licences
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|other
task_categories:
  - token-classification
  - text-generation
task_ids:
  - natural-language-inference
pretty_name: String Operations
tags:
  - development
  - NLU
  - small scale
dataset_info:
  - config_name: small
    features:
      - name: input
        dtype: string
      - name: output
        dtype: string
      - name: code
        dtype: string
      - name: res_var
        dtype: string
      - name: operation
        dtype: string
      - name: id
        dtype: int32
    splits:
      - name: train
        num_bytes: 3222948
        num_examples: 33939
      - name: test
        num_bytes: 1392252
        num_examples: 14661
    download_size: 1178254
    dataset_size: 4615200
  - config_name: small10
    features:
      - name: input
        dtype: string
      - name: output
        dtype: string
      - name: code
        dtype: string
      - name: res_var
        dtype: string
      - name: operation
        dtype: string
      - name: id
        dtype: int32
    splits:
      - name: train
        num_bytes: 956996
        num_examples: 11313
      - name: test
        num_bytes: 413404
        num_examples: 4887
    download_size: 312419
    dataset_size: 1370400
  - config_name: small15
    features:
      - name: input
        dtype: string
      - name: output
        dtype: string
      - name: code
        dtype: string
      - name: res_var
        dtype: string
      - name: operation
        dtype: string
      - name: id
        dtype: int32
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        num_examples: 11313
      - name: test
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        num_examples: 4887
    download_size: 393420
    dataset_size: 1538400
  - config_name: small20
    features:
      - name: input
        dtype: string
      - name: output
        dtype: string
      - name: code
        dtype: string
      - name: res_var
        dtype: string
      - name: operation
        dtype: string
      - name: id
        dtype: int32
    splits:
      - name: train
        num_bytes: 1191636
        num_examples: 11313
      - name: test
        num_bytes: 514764
        num_examples: 4887
    download_size: 472415
    dataset_size: 1706400

Dataset Card for Small String Operations Dataset

Dataset Description

Homepage: PaDaS Lab
Repository:
Paper:
Leaderboard:
Point of Contact: Michael Granitzer, michael.granitzer@uni-passau.de

Other Metadata

Dataset Summary

Minimal dataset for intended for LM development and testing using python string operations. The dataset is created by running different one line python string operations on random strings The idea is, that transformer implementation can learn the string operations and that this task is a good proxy tasks for other transformer operations on real languages and real tasks. Consequently, the data set is small and can be used in the development process without large scale infrastructures.

Dataset Structure

Data Instances

There are different configurations for the data set.

small: contains below 50k instances of various string length and only contains slicing operations, i.e. all python operations expressable with s[i:j:s] (which also includes string reversal).
- you can further choose different subsets according to either length or the kind of operation

Data Fields

all data instances can be found under the field "data".

input: input string, i.e. the string and the string operation
output: output of the string operation
code: code for running the string operation in python,
res_var: name of the result variable
operation: kind of operation:
- step_x for s[::x]
- char_at_x for s[x]
- slice_x:y for s[x:y]
- slice_step_x:y:z for s[x:y:z]
- slice_reverse_i:j:k for s[i:i+j][::k]

Siblings of data contain additional metadata information about the dataset.

prompt describes possible prompts based on that data splitted into input prompts / output prompts

Data Splits

The dataset is split into a train and test split for different string lengths

Dataset Creation

The dataset is synthetically created

Licensing Information

MIT License

Citation Information

[More Information Needed]

Contributions

Chair of Data Science, University of Passau

Michael Granitzer, University of Passau

Thanks to @mgrani for adding this dataset. """

Acknowledgements

This work is part of the OpenWebSearch.eu project and the SMAEGBot Project. The OpenWebSearch.eu Project is funded by the EU under the GA 101070014 and we thank the EU for their support. SMAEGBot is supported by funds of the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany. The Federal Office for Agriculture and Food (BLE) provides coordinating support for artificial intelligence (AI) in agriculture as funding organisation, grant number 05119082.