Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
extended|other-reuters-corpus
License:
# Inspired by conll2003 dataset | |
# https://huggingface.co/datasets/conll2003 | |
# coding=utf-8 | |
# Copyright 2020 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 | |
"""Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition""" | |
import os | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """\ | |
@inproceedings{tjong-kim-sang-de-meulder-2003-introduction, | |
title = "Introduction to the {C}o{NLL}-2003 Shared Task: Language-Independent Named Entity Recognition", | |
author = "Tjong Kim Sang, Erik F. and | |
De Meulder, Fien", | |
booktitle = "Proceedings of the Seventh Conference on Natural Language Learning at {HLT}-{NAACL} 2003", | |
year = "2003", | |
url = "https://www.aclweb.org/anthology/W03-0419", | |
pages = "142--147", | |
} | |
""" | |
_DESCRIPTION = """\ | |
The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on | |
four types of named entities: persons, locations, organizations and names of miscellaneous entities that do | |
not belong to the previous three groups. | |
The CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on | |
a separate line and there is an empty line after each sentence. The first item on each line is a word, the second | |
a part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags | |
and the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only | |
if two phrases of the same type immediately follow each other, the first word of the second phrase will have tag | |
B-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2 | |
tagging scheme, whereas the original dataset uses IOB1. | |
For more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419 | |
""" | |
_URL = "https://data.deepai.org/conll2003.zip" | |
_TRAINING_FILE = "train.txt" | |
_DEV_FILE = "valid.txt" | |
_TEST_FILE = "test.txt" | |
# class Conll2003Config(datasets.BuilderConfig): | |
# """BuilderConfig for Conll2003""" | |
# def __init__(self, **kwargs): | |
# """BuilderConfig forConll2003. | |
# Args: | |
# **kwargs: keyword arguments forwarded to super. | |
# """ | |
# super(Conll2003Config, self).__init__(**kwargs) | |
class Conll2003(datasets.GeneratorBasedBuilder): | |
# """Conll2003 dataset.""" | |
# BUILDER_CONFIGS = [ | |
# Conll2003Config(name="conll2003", version=datasets.Version( | |
# "1.0.0"), description="Conll2003 dataset"), | |
# ] | |
VERSION = datasets.Version("1.1.0") | |
DEFAULT_CONFIG_NAME = "first_domain" | |
BUILDER_CONFIGS = [ | |
# datasets.BuilderConfig(name="first_domain", version=VERSION, | |
# description="This part of my dataset covers a first domain"), | |
# datasets.BuilderConfig(name="second_domain", version=VERSION, | |
# description="This part of my dataset covers a second domain"), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"tokens": datasets.Sequence(datasets.Value("string")), | |
"ner_tags": datasets.Sequence( | |
datasets.features.ClassLabel( | |
names=[ | |
"O", | |
"B-PER", | |
"I-PER", | |
"B-TAG", | |
"I-TAG", | |
"B-LOC", | |
"I-LOC", | |
"B-TIME", | |
"I-TIME", | |
"B-SORT", | |
"I-SORT" | |
] | |
) | |
), | |
} | |
), | |
supervised_keys=None, | |
homepage="https://www.aclweb.org/anthology/W03-0419/", | |
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, _TRAINING_FILE), | |
# "dev": os.path.join(downloaded_file, _DEV_FILE), | |
# "test": os.path.join(downloaded_file, _TEST_FILE), | |
# } | |
# data_files = { | |
# "train": os.path.join(downloaded_file, _TRAINING_FILE), | |
# "dev": os.path.join(downloaded_file, _DEV_FILE), | |
# "test": os.path.join(downloaded_file, _TEST_FILE), | |
# } | |
url = "https://pastebin.pl/view/raw/f1bffd94" | |
text_file = dl_manager.download(url) | |
data_files = { | |
"train": text_file, | |
"dev": text_file, | |
"test": text_file, | |
} | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={ | |
"filepath": data_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={ | |
"filepath": data_files["dev"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={ | |
"filepath": data_files["test"]}), | |
] | |
def _generate_examples(self, filepath): | |
logger.info("⏳ Generating examples from = %s", filepath) | |
with open(filepath, encoding="utf-8") as f: | |
guid = 0 | |
tokens = [] | |
pos_tags = [] | |
chunk_tags = [] | |
ner_tags = [] | |
for line in f: | |
if line.startswith("-DOCSTART-") or line == "" or line == "\n": | |
if tokens: | |
yield guid, { | |
"id": str(guid), | |
"tokens": tokens, | |
"ner_tags": ner_tags, | |
} | |
guid += 1 | |
tokens = [] | |
ner_tags = [] | |
else: | |
# conll2003 tokens are space separated | |
splits = line.split(" ") | |
tokens.append(splits[0]) | |
ner_tags.append(splits[1].rstrip()) | |
# last example | |
if tokens: | |
yield guid, { | |
"id": str(guid), | |
"tokens": tokens, | |
"ner_tags": ner_tags, | |
} | |