Datasets:
Tasks:
Text2Text Generation
Languages:
English
import csv | |
import json | |
# Lint as: python3 | |
import os | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """ | |
@article{Xu-EtAl:2016:TACL, | |
author = {Wei Xu and Courtney Napoles and Ellie Pavlick and Quanze Chen and Chris Callison-Burch}, | |
title = {Optimizing Statistical Machine Translation for Text Simplification}, | |
journal = {Transactions of the Association for Computational Linguistics}, | |
volume = {4}, | |
year = {2016}, | |
url = {https://cocoxu.github.io/publications/tacl2016-smt-simplification.pdf}, | |
pages = {401--415} | |
} | |
""" | |
_DESCRIPTION = """Corpus of sentences gathered from Wikipedia and simplifications proposed by Amazon MTurk workers. | |
Data gathered by Wei Xu, Courtney Napoles, Ellie Pavlick, Quanze Chen and Chris Callison-Burch.""" | |
_URLS = { | |
"tune": "https://huggingface.co./datasets/waboucay/turk_corpus/raw/main/tune.8turkers.organized.tsv", | |
"test": "https://huggingface.co./datasets/waboucay/turk_corpus/raw/main/test.8turkers.organized.tsv" | |
} | |
_TUNE_FILE = "tune.json" | |
_TEST_FILE = "test.json" | |
class TurkCorpusConfig(datasets.BuilderConfig): | |
"""BuilderConfig for WikiLarge dataset""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for Turk Corpus dataset | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(TurkCorpusConfig, self).__init__(**kwargs) | |
class TurkCorpus(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.0.0", "") | |
BUILDER_CONFIG_CLASS = TurkCorpusConfig | |
BUILDER_CONFIGS = [ | |
TurkCorpusConfig( | |
name="turk_corpus", | |
version=datasets.Version("1.0.0", ""), | |
description=_DESCRIPTION, | |
) | |
] | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"complex": datasets.Value("string"), | |
"simple": datasets.Sequence(datasets.Value("string")), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage="https://github.com/cocoxu/simplification/tree/master", | |
) | |
def _split_generators(self, dl_manager): | |
dl_files = dl_manager.download(_URLS) | |
tune_path = os.path.join(os.path.dirname(dl_files["test"]), _TUNE_FILE) | |
test_path = os.path.join(os.path.dirname(dl_files["test"]), _TEST_FILE) | |
tune_data_path = os.path.abspath(dl_files["tune"]) | |
test_data_path = os.path.abspath(dl_files["test"]) | |
with open(tune_data_path, encoding="utf-8") as tune_data, open(test_data_path, encoding="utf-8") as test_data, \ | |
open(tune_path, "w", encoding="utf-8") as tune_json, open(test_path, "w", encoding="utf-8") as test_json: | |
tune_reader = csv.reader(tune_data, delimiter="\t") | |
test_reader = csv.reader(test_data, delimiter="\t") | |
tune_data = [] | |
for line in tune_reader: | |
tune_data.append({"complex": line[1], "simple": line[2:]}) | |
json.dump(tune_data, tune_json) | |
test_data = [] | |
for line in test_reader: | |
test_data.append({"complex": line[1], "simple": line[2:]}) | |
json.dump(test_data, test_json) | |
data_files = { | |
"tune": tune_path, | |
"test": test_path, | |
} | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["tune"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}), | |
] | |
def _generate_examples(self, filepath): | |
"""This function returns the examples in the raw (text) form.""" | |
with open(filepath, encoding="utf-8") as f: | |
guid = 0 | |
data = json.load(f) | |
for obj in data: | |
yield guid, { | |
"complex": obj["complex"], | |
"simple": obj["simple"] | |
} | |
guid += 1 | |