Datasets:
Tasks:
Other
Languages:
Swedish
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
other
Annotations Creators:
expert-generated
Source Datasets:
original
License:
# coding=utf-8 | |
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# Lint as: python3 | |
"""The SuperGLUE benchmark.""" | |
import json | |
import os | |
import datasets | |
_CITATION = """\ | |
@article{gustafson2006documentation, | |
title={Documentation of the Stockholm-Ume{\aa} Corpus}, | |
author={Gustafson-Capkov{\'a}, Sofia and Hartmann, Britt}, | |
journal={Stockholm University: Department of Linguistics}, | |
year={2006} | |
} | |
""" | |
# You can copy an official description | |
_DESCRIPTION = """\ | |
The dataset is a conversion of the venerable SUC 3.0 dataset into the | |
huggingface ecosystem. The original dataset does not contain an official | |
train-dev-test split, which is introduced here; the tag distribution for the | |
NER tags between the three splits is mostly the same. | |
The dataset has three different types of tagsets: manually annotated POS, | |
manually annotated NER, and automatically annotated NER. For the | |
automatically annotated NER tags, only sentences were chosen, where the | |
automatic and manual annotations would match (with their respective | |
categories). | |
Additionally we provide remixes of the same data with some or all sentences | |
being lowercased. | |
""" | |
_HOMEPAGE = "https://spraakbanken.gu.se/en/resources/suc3" | |
_LICENSE = "CC-BY-4.0" | |
# TODO: Add link to the official dataset URLs here | |
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
# _URL = "https://huggingface.co/datasets/KBLab/suc3_1/resolve/main/data/" | |
_URL = "https://huggingface.co/datasets/KBLab/sucx3_ner/resolve/main/data/" | |
_URLS = { | |
"original_tags": { | |
"cased": "original_tags/cased.tar.gz", | |
"lower": "original_tags/lower.tar.gz", | |
"lower_mix": "original_tags/lower_mix.tar.gz"}, | |
"simple_tags": { | |
"cased": "simple_tags/cased.tar.gz", | |
"lower": "simple_tags/lower.tar.gz", | |
"lower_mix": "simple_tags/lower_mix.tar.gz"} | |
} | |
_POS_LABEL_NAMES = { | |
'AB', 'DT', 'HA', 'HD', 'HP', 'HS', 'IE', 'IN', 'JJ', 'KN', 'MAD', 'MID', | |
'NN', 'PAD', 'PC', 'PL', 'PM', 'PN', 'PP', 'PS', 'RG', 'RO', 'SN', 'UO', | |
'VB' | |
} | |
_NER_LABEL_NAMES_ORIGINAL = { | |
'B-animal', 'B-event', 'B-inst', 'B-myth', 'B-other', 'B-person', | |
'B-place', 'B-product', 'B-work', 'I-animal', 'I-event', 'I-inst', | |
'I-myth', 'I-other', 'I-person', 'I-place', 'I-product', 'I-work', 'O' | |
} | |
_NER_LABEL_NAMES_SIMPLE = { | |
'B-EVN', 'B-LOC', 'B-MSR', 'B-OBJ', 'B-ORG', 'B-PRS', 'B-TME', 'B-WRK', | |
'I-EVN', 'I-LOC', 'I-MSR', 'I-OBJ', 'I-ORG', 'I-PRS', 'I-TME', 'I-WRK', 'O' | |
} | |
class SUC3Config(datasets.BuilderConfig): | |
"""BuilderConfig for Suc.""" | |
def __init__(self, | |
ner_label_names, | |
description, | |
data_url, | |
**kwargs): | |
"""BuilderConfig for Suc. | |
""" | |
super(SUC3Config, | |
self).__init__(version=datasets.Version("1.0.2"), **kwargs) | |
self.ner_label_names = ner_label_names | |
self.description = description | |
self.data_url = data_url | |
class SUC3(datasets.GeneratorBasedBuilder): | |
"""The SuperGLUE benchmark.""" | |
BUILDER_CONFIGS = [ | |
SUC3Config( | |
name="original_cased", | |
ner_label_names=_NER_LABEL_NAMES_ORIGINAL, | |
data_url=_URLS["original_tags"]["cased"], | |
description="manually annotated & cased", | |
), | |
SUC3Config( | |
name="original_lower", | |
ner_label_names=_NER_LABEL_NAMES_ORIGINAL, | |
data_url=_URLS["original_tags"]["lower"], | |
description="manually annotated & lower", | |
), | |
SUC3Config( | |
name="original_lower_mix", | |
ner_label_names=_NER_LABEL_NAMES_ORIGINAL, | |
data_url=_URLS["original_tags"]["lower_mix"], | |
description="manually annotated & lower_mix", | |
), | |
SUC3Config( | |
name="simple_cased", | |
ner_label_names=_NER_LABEL_NAMES_SIMPLE, | |
data_url=_URLS["simple_tags"]["cased"], | |
description="automatically annotated & cased", | |
), | |
SUC3Config( | |
name="simple_lower", | |
ner_label_names=_NER_LABEL_NAMES_SIMPLE, | |
data_url=_URLS["simple_tags"]["lower"], | |
description="automatically annotated & lower", | |
), | |
SUC3Config( | |
name="simple_lower_mix", | |
ner_label_names=_NER_LABEL_NAMES_SIMPLE, | |
data_url=_URLS["simple_tags"]["lower_mix"], | |
description="autimatically annotated & lower_mix", | |
), | |
] | |
def _info(self): | |
features = {"id": datasets.Value("string"), | |
"tokens": datasets.features.Sequence(datasets.Value("string")), | |
"pos_tags": datasets.features.Sequence(datasets.Value("string")), | |
"ner_tags": datasets.features.Sequence(datasets.Value("string"))} | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION + self.config.description, | |
features=datasets.Features(features), | |
homepage=_HOMEPAGE, | |
citation=_CITATION, | |
supervised_keys=None, | |
) | |
def _split_generators(self, dl_manager): | |
dl_dir = dl_manager.download_and_extract(_URL + self.config.data_url) | |
dl_dir = os.path.join(dl_dir, self.config.data_url.split("/")[-1].split(".")[0]) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"data_file": os.path.join(dl_dir, "train.jsonl"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"data_file": os.path.join(dl_dir, "dev.jsonl"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"data_file": os.path.join(dl_dir, "test.jsonl"), | |
}, | |
), | |
] | |
def _generate_examples(self, data_file): | |
with open(data_file, encoding="utf-8") as f: | |
for i, line in enumerate(f): | |
row = json.loads(line) | |
yield str(i), row | |