|
import json |
|
import bz2 |
|
|
|
import datasets |
|
from datasets import DownloadManager, DatasetInfo |
|
|
|
|
|
def _order_langs(lang1, lang2): |
|
return (lang1, lang2) if lang1 < lang2 else (lang2, lang1) |
|
|
|
|
|
class WSDMTConfig(datasets.BuilderConfig): |
|
def __init__(self, *args, corpus, lang1, lang2, variety='base', **kwargs): |
|
lang1, lang2 = _order_langs(lang1, lang2) |
|
super().__init__( |
|
*args, |
|
name=f"{corpus}@{lang1}-{lang2}@{variety}", |
|
**kwargs, |
|
) |
|
self.lang1 = lang1 |
|
self.lang2 = lang2 |
|
self.corpus = corpus |
|
self.variety = variety |
|
|
|
def path_for(self, split, lang): |
|
return f"data/{self.corpus}/{self.variety}/{split}/{lang}.jsonl.bz2" |
|
|
|
|
|
POS_TAGS = """ADJ ADP |
|
ADV |
|
AUX |
|
CCONJ |
|
DET |
|
INTJ |
|
NOUN |
|
NUM |
|
PART |
|
PRON |
|
PROPN |
|
PUNCT |
|
SCONJ |
|
SYM |
|
VERB |
|
X""".splitlines() |
|
|
|
|
|
class WSDMTDataset(datasets.GeneratorBasedBuilder): |
|
BUILDER_CONFIG_CLASS = WSDMTConfig |
|
config: WSDMTConfig |
|
|
|
def _generate_examples(self, path_lang1, path_lang2): |
|
with bz2.open(path_lang1) as f1, bz2.open(path_lang2) as f2: |
|
for n, (line1, line2) in enumerate(zip(f1, f2)): |
|
sid1, data1 = self._read_json_line(line1) |
|
sid2, data2 = self._read_json_line(line2) |
|
|
|
assert sid1 == sid2, ( |
|
f"Different sentence id found for {self.config.lang1} and {self.config.lang2}: " |
|
f"{sid1} != {sid2} at line {n}" |
|
) |
|
|
|
data_dict = { |
|
'sid': sid1, |
|
self.config.lang1: data1, |
|
self.config.lang2: data2, |
|
} |
|
|
|
yield n, data_dict |
|
|
|
@classmethod |
|
def _read_json_line(cls, line): |
|
obj = json.loads(line) |
|
sid = obj.pop('sid') |
|
sentence = obj.pop('sentence') |
|
data = obj.pop('data') |
|
tokens, lemmas, pos_tags, senses, is_senses, is_polysemous = zip(*data) |
|
assert len(tokens) == len(lemmas) == len(pos_tags) == len(senses) == len(is_senses) == len(is_polysemous), ( |
|
f"Inconsistent annotation lengths in sentence {sid}" |
|
) |
|
|
|
return sid, dict( |
|
sentence=sentence, |
|
tokens=tokens, lemmas=lemmas, pos_tags=pos_tags, |
|
sense=senses, identified_as_sense=is_senses, is_polysemous=is_polysemous, |
|
) |
|
|
|
def _info(self) -> DatasetInfo: |
|
language_features = dict( |
|
sentence=datasets.Value("string"), |
|
tokens=datasets.Sequence(datasets.Value("string")), |
|
sense=datasets.Sequence(datasets.Value("string")), |
|
identified_as_sense=datasets.Sequence(datasets.Value("bool")), |
|
is_polysemous=datasets.Sequence(datasets.Value("bool")), |
|
lemmas=datasets.Sequence(datasets.Value("string")), |
|
pos_tags=datasets.Sequence(datasets.ClassLabel(names=POS_TAGS)), |
|
|
|
) |
|
|
|
return datasets.DatasetInfo( |
|
description="empty description", |
|
features=datasets.Features( |
|
{ |
|
"sid": datasets.Value("string"), |
|
self.config.lang1: language_features, |
|
self.config.lang2: language_features |
|
}, |
|
), |
|
supervised_keys=None, |
|
homepage="no-homepage", |
|
citation="no-citation", |
|
) |
|
|
|
def _split_generators(self, dl_manager: DownloadManager): |
|
splits_file = dl_manager.download(f'data/{self.config.corpus}/splits.txt') |
|
|
|
with open(splits_file) as f: |
|
split_names = [line.rstrip() for line in f] |
|
|
|
urls = { |
|
split: { |
|
self.config.lang1: self.config.path_for(split, self.config.lang1), |
|
self.config.lang2: self.config.path_for(split, self.config.lang2), |
|
} |
|
for split in split_names |
|
} |
|
downloaded = dl_manager.download(urls) |
|
|
|
return [ |
|
datasets.SplitGenerator(name=split, |
|
gen_kwargs=dict( |
|
path_lang1=paths[self.config.lang1], |
|
path_lang2=paths[self.config.lang2], |
|
)) |
|
for split, paths in downloaded.items() |
|
] |
|
|
