Datasets:
Tasks:
Token Classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
License:
# coding=utf-8 | |
# Copyright 2022 Leon Derczynski | |
# | |
# 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 | |
"""Named Temporal Expressions corpus (English)""" | |
import os | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """\ | |
@inproceedings{brucato-etal-2013-recognising, | |
title = "Recognising and Interpreting Named Temporal Expressions", | |
author = "Brucato, Matteo and | |
Derczynski, Leon and | |
Llorens, Hector and | |
Bontcheva, Kalina and | |
Jensen, Christian S.", | |
booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing {RANLP} 2013", | |
month = sep, | |
year = "2013", | |
address = "Hissar, Bulgaria", | |
publisher = "INCOMA Ltd. Shoumen, BULGARIA", | |
url = "https://aclanthology.org/R13-1015", | |
pages = "113--121", | |
} | |
""" | |
_DESCRIPTION = """\ | |
This is a dataset annotated for _named temporal expression_ chunks. | |
The | |
commonest temporal expressions typically | |
contain date and time words, like April or | |
hours. Research into recognising and interpreting these typical expressions is mature in many languages. However, there is | |
a class of expressions that are less typical, | |
very varied, and difficult to automatically | |
interpret. These indicate dates and times, | |
but are harder to detect because they often do not contain time words and are not | |
used frequently enough to appear in conventional temporally-annotated corpora – | |
for example *Michaelmas* or *Vasant Panchami*. | |
For more details see [https://aclanthology.org/R13-1015.pdf](https://aclanthology.org/R13-1015.pdf) | |
""" | |
_URL = "http://www.derczynski.com/resources/named_timex.tar.bz2" | |
_TRAIN_FILE = "ntimex-train.conll" | |
_TEST_FILE = "ntimex-eval.conll" | |
class NamedTimexesConfig(datasets.BuilderConfig): | |
"""BuilderConfig for NamedTimexes""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for NamedTimexes. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(NamedTimexesConfig, self).__init__(**kwargs) | |
class NamedTimexes(datasets.GeneratorBasedBuilder): | |
"""NamedTimexes dataset.""" | |
BUILDER_CONFIGS = [ | |
NamedTimexesConfig(name="named-timexes", version=datasets.Version("1.0.0"), description="Named Temporal Expressions dataset"), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"tokens": datasets.Sequence(datasets.Value("string")), | |
"ntimex_tags": datasets.Sequence( | |
datasets.features.ClassLabel( | |
names=[ | |
"O", | |
"T", | |
] | |
) | |
), | |
} | |
), | |
supervised_keys=None, | |
homepage="https://aclanthology.org/R13-1015.pdf", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
downloaded_file = dl_manager.download_and_extract(_URL) | |
data_files = { | |
"train": os.path.join(downloaded_file, _TRAIN_FILE), | |
"test": os.path.join(downloaded_file, _TEST_FILE), | |
} | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}), | |
] | |
def _generate_examples(self, filepath): | |
guid = 0 | |
with open(filepath, encoding="utf-8") as f: | |
logger.info("⏳ Generating examples from = %s", filepath) | |
tokens = [] | |
ntimex_tags = [] | |
for line in f: | |
if line.startswith("-DOCSTART-") or line.strip() == "" or line == "\n": | |
if tokens: | |
yield guid, { | |
"id": str(guid), | |
"tokens": tokens, | |
"ntimex_tags": ntimex_tags, | |
} | |
guid += 1 | |
tokens = [] | |
ntimex_tags = [] | |
else: | |
# btc entries are tab separated | |
fields = line.split("\t") | |
tokens.append(fields[0]) | |
ntimex_tags.append(fields[1].rstrip()) | |
# last example | |
yield guid, { | |
"id": str(guid), | |
"tokens": tokens, | |
"ntimex_tags": ntimex_tags, | |
} | |