Skip to main content

gec-datasets

This library is to handle datasets of Grammatical Error Correction.

Install

pip install gec-datasets

Usage

API

from gec_datasets import GECDatasets
gec = GECDatasets(
    base_path='gec_datasets_base/'
)
conll14 = gec.load('conll14')

assert conll14.srcs is not None
assert conll14.refs is not None
# The number of sentences is 1312.
assert len(conll14.srcs) == 1312
# CoNLL-2014 contains two official references.
assert len(conll14.refs) == 2
# Each reference also contains 1312 sentences.
assert len(conll14.refs[0]) == 1312
assert len(conll14.refs[1]) == 1312

Available ids can be found by:

import gec_datasets
print(gec_datasets.available())

CLI

You can specify multiple ids of the data you want to download in the --ids field.

gecdatasets-download --base_path "gec_datasets_base/" --ids conll14 bea19-dev

Available ids can be found by:

gecdatasets-available

In both API and CLI, datasets will be stored under base_path=.
The first time it is downloaded automatically, and thereafter it is loaded from the saved files.

When you call gec.load('sample'), gec-datasets simply refers to <base_path>/'sample'/{src.txt|ref0.txt|...}.

gec_datasets_base/
├── conll14
│   ├── ref0.txt
│   ├── ref1.txt
│   └── src.txt
├── bea19-dev
│   ├── ref0.txt
│   ├── src.txt
├── bea19-test
│   └── src.txt
...

Supported datasets

Public datasets

ID .load(ID) Description
'conll13' CoNLL-2013 test set [Ng+ 2013].
'conll14' CoNLL-2014 test set [Ng+ 2014].
'jfleg-test' JFLEG test set [Napoles+ 2017].
'jfleg-dev' JFLEG development set [Napoles+ 2017].
'fce-test' FCE test set [Yannakoudakis+ 2011]
'fce-dev' FCE development set [Yannakoudakis+ 2011].
'fce-train' FCE training set [Yannakoudakis+ 2011].
'cweb-g-test' CWEB-G test set [Flachs+ 2020].
'cweb-g-dev' CWEB-G development set [Flachs+ 2020].
'cweb-s-test' CWEB-S test set [Flachs+ 2020].
'cweb-s-dev' CWEB-S development set [Flachs+ 2020].
'bea19-test' BEA-2019 shared task test set [Bryant+ 2019].
'bea19-dev' BEA-2019 shared task development set [Bryant+ 2019]. It contains only source sentences.
'wi-locness-train' W&I+LOCNESS training set [Yannakoudakis+ 2018].

The following is synthetic data.

ID .load(ID) Description
'troy-1bw-train' Synthetic data based on the One Billion Words Benchmark for distillation [Tarnavskyi,+ 2022].
'troy-1bw-dev' Another split of the synthetic data based on the One Billion Words Benchmark for distillation [Tarnavskyi,+ 2022].
'troy-blogs-train' Synthetic data based on the Blog Authorship Corpus for distillation [Tarnavskyi,+ 2022].
'troy-blogs-dev' Another split of the synthetic data based on the Blog Authorship Corpus for distillation [Tarnavskyi,+ 2022].
'pie-synthetic-a1' Synthetic data based on the One Billion Words Benchmark [Awasthi+ 19]. You can also specify a2, a3, a4, and a5. This attachment describes how to make synthetic errors.

Non-public datasets

ID .load(ID) Description
'nucle-train' NUCLE training set. [Dahlmeier+ 2013]
'lang8-train' Lang-8 training set. [Mizumoto+ 2012] [Tajiri+ 2012]

nucle-train

  • Request data from HERE.
  • You will receive an email with release3.3.tar.bz2 attached.
  • mkdir <base_path>/nucle/ and put the data as <base_path>/nucle/release3.3.tar.bz2.
  • You can now use the data with .load("nucle-train"). The data will be extracted automatically.

lang8-train

  • Request data from HERE.
  • You will receive an email titled "[NAIST Lang-8 Corpus of Learner English for the 14th BEA Shared Task]".
  • mkdir <base_path>/lang8/ and put the data as <base_path>/lang8/lang8.bea19.tar.gz.
  • You can now use the data with .load("lang8-train"). The data will be extracted automatically.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gec_datasets-0.2.0.tar.gz (9.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gec_datasets-0.2.0-py3-none-any.whl (15.9 kB view details)

Uploaded Python 3

File details

Details for the file gec_datasets-0.2.0.tar.gz.

File metadata

  • Download URL: gec_datasets-0.2.0.tar.gz
  • Upload date:
  • Size: 9.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.11

File hashes

Hashes for gec_datasets-0.2.0.tar.gz
Algorithm Hash digest
SHA256 6b173d56bf8066b70f56af7a98e8985bf8975510f8b82bc3e307dc7780ca71e7
MD5 3d9bd722dce28c348d9d2fb19a8b0b9d
BLAKE2b-256 255f31d3604928bcc79f79204019034a95344e1dddf1ab2485598034498dac19

See more details on using hashes here.

File details

Details for the file gec_datasets-0.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for gec_datasets-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f9b22bc0c132b58db9ee109b4bf6116682814a8709dbbb5d3700da8055c0d035
MD5 c1c4a59eae0e085cfee95d257707673d
BLAKE2b-256 6a9f6923752e36023c6a1ee7a3c4a06b2d80777ed0ca7f3aa3aec14cd70ab90d

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.2.0 This release

2 files

0.1.1

2 files

0.1.0

2 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page