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# coding=utf-8
'''DiscEvalMT: DiscEvalMT: Contrastive test sets for the evaluation of discourse in machine translation (v2)'''
import json
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = '''\
@inproceedings{bawden-etal-2018-evaluating,
title = "Evaluating Discourse Phenomena in Neural Machine Translation",
author = "Bawden, Rachel and Sennrich, Rico and Birch, Alexandra and Haddow, Barry",
booktitle = {{Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)}},
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/N18-1118",
doi = "10.18653/v1/N18-1118",
pages = "1304--1313"
}
'''
_DESCRIPTION = '''\
English-French hand-crafted contrastive test set to test anaphora and lexical choice
'''
_HOMEPAGE='https://github.com/rbawden/discourse-mt-test-sets/tree/master'
_LICENSE = 'CC-BY-SA-4.0'
_URLS = {
'test-lexical_choice': 'lexical_choice/eval.jsonl',
'test-anaphora': 'anaphora/eval.jsonl'
}
class DiscEvalMTConfig(datasets.BuilderConfig):
'''BuilderConfig for DiscEvalMT.'''
def __init__(self, evaltype: str, **kwargs):
"""BuilderConfig for DiscEvalMT.
Args:
**kwargs: keyword arguments forwarded to super.
"""
self.evaltype = evaltype
if evaltype not in ['anaphora', 'lexical_choice']:
raise ValueError("Invalid evaltype: %s. You must choose between 'anaphora' and 'lexical_choice' " % evaltype)
super(DiscEvalMTConfig, self).__init__(**kwargs)
class DiscEvalMT(datasets.GeneratorBasedBuilder):
'''DiscEvalMT: English-French contrastive test set for 2 discourse phenomena (anaphora and lexical cohesion)'''
BUILDER_CONFIG_CLASS = DiscEvalMTConfig
BUILDER_CONFIGS = [
DiscEvalMTConfig(
evaltype='anaphora',
name='anaphora',
version=datasets.Version('2.0.0'),
),
DiscEvalMTConfig(
evaltype='lexical_choice',
name='lexical_choice',
version=datasets.Version('2.0.0'),
),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features({
"split": datasets.Value("string"),
"ex_num": datasets.Value("int64"),
"type": datasets.Value("string"),
"context_src": datasets.Value("string"),
"current_src": datasets.Value("string"),
"context_trg": datasets.Value("string"),
"current_trg": datasets.Value("string"),
"contrastive_context_trg": datasets.Value("string"),
"contrastive_current_trg": datasets.Value("string"),
"correct_or_semicorrect": datasets.Value("string")}),
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
license=_LICENSE,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download_and_extract(_URLS)
return datasets.SplitGenerator(name="test", gen_kwargs={'filepath': downloaded_files['test-' + self.config.evaltype]}),
def _generate_examples(self, filepath):
logger.info("generating examples from = %s", filepath)
key = 0
with open(filepath, encoding="utf-8") as f:
for i, line in enumerate(f):
example = json.loads(line)
yield i, example
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