albertvillanova HF staff commited on
Commit
dc06405
1 Parent(s): fe41a26

Convert dataset to Parquet (#5)

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- Convert dataset to Parquet (5d70f102c0f52f4ac8a8d14e200c8c39c61496e7)
- Delete loading script (821c1c4984fe61856b44e362f865c751f28e58c5)

README.md CHANGED
@@ -42,8 +42,18 @@ dataset_info:
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  - name: test
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  num_bytes: 2454589
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  num_examples: 5000
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- download_size: 4636753
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  dataset_size: 9765631
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for bc2gm_corpus
 
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  - name: test
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  num_bytes: 2454589
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  num_examples: 5000
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+ download_size: 2154630
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  dataset_size: 9765631
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+ configs:
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+ - config_name: bc2gm_corpus
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+ data_files:
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+ - split: train
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+ path: bc2gm_corpus/train-*
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+ - split: validation
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+ path: bc2gm_corpus/validation-*
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+ - split: test
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+ path: bc2gm_corpus/test-*
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+ default: true
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  ---
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  # Dataset Card for bc2gm_corpus
bc2gm_corpus.py DELETED
@@ -1,143 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 HuggingFace Datasets Authors.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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-
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- # Lint as: python3
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- """BioCreative II gene mention recognition Corpus"""
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-
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- import datasets
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-
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-
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- logger = datasets.logging.get_logger(__name__)
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-
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-
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- _CITATION = """\
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- @article{smith2008overview,
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- title={Overview of BioCreative II gene mention recognition},
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- author={Smith, Larry and Tanabe, Lorraine K and nee Ando, Rie Johnson and Kuo, Cheng-Ju and Chung, I-Fang and Hsu, Chun-Nan and Lin, Yu-Shi and Klinger, Roman and Friedrich, Christoph M and Ganchev, Kuzman and others},
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- journal={Genome biology},
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- volume={9},
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- number={S2},
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- pages={S2},
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- year={2008},
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- publisher={Springer}
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- }
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- """
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-
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- _DESCRIPTION = """\
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- Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop.
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- In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions.
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- A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721.
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- Here we present brief descriptions of all the methods used and a statistical analysis of the results.
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- We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible,
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- and furthermore that the best result makes use of the lowest scoring submissions.
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-
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- For more details, see: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/
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-
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- The original dataset can be downloaded from: https://biocreative.bioinformatics.udel.edu/resources/corpora/biocreative-ii-corpus/
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- This dataset has been converted to CoNLL format for NER using the following tool: https://github.com/spyysalo/standoff2conll
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- """
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-
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- _HOMEPAGE = "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/"
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- _URL = "https://github.com/spyysalo/bc2gm-corpus/raw/master/conll/"
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- _TRAINING_FILE = "train.tsv"
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- _DEV_FILE = "devel.tsv"
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- _TEST_FILE = "test.tsv"
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-
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-
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- class Bc2gmCorpusConfig(datasets.BuilderConfig):
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- """BuilderConfig for Bc2gmCorpus"""
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-
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- def __init__(self, **kwargs):
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- """BuilderConfig for Bc2gmCorpus.
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- Args:
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- **kwargs: keyword arguments forwarded to super.
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- """
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- super(Bc2gmCorpusConfig, self).__init__(**kwargs)
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-
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-
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- class Bc2gmCorpus(datasets.GeneratorBasedBuilder):
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- """Bc2gmCorpus dataset."""
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-
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- BUILDER_CONFIGS = [
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- Bc2gmCorpusConfig(name="bc2gm_corpus", version=datasets.Version("1.0.0"), description="bc2gm corpus"),
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- ]
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-
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- def _info(self):
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
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- "id": datasets.Value("string"),
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- "tokens": datasets.Sequence(datasets.Value("string")),
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- "ner_tags": datasets.Sequence(
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- datasets.features.ClassLabel(
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- names=[
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- "O",
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- "B-GENE",
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- "I-GENE",
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- ]
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- )
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- ),
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- }
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- ),
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- supervised_keys=None,
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- homepage=_HOMEPAGE,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- urls_to_download = {
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- "train": f"{_URL}{_TRAINING_FILE}",
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- "dev": f"{_URL}{_DEV_FILE}",
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- "test": f"{_URL}{_TEST_FILE}",
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- }
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- downloaded_files = dl_manager.download_and_extract(urls_to_download)
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-
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- return [
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- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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- datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
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- datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
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- ]
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-
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- def _generate_examples(self, filepath):
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- logger.info("⏳ Generating examples from = %s", filepath)
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- with open(filepath, encoding="utf-8") as f:
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- guid = 0
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- tokens = []
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- ner_tags = []
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- for line in f:
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- if line == "" or line == "\n":
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- if tokens:
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- yield guid, {
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- "id": str(guid),
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- "tokens": tokens,
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- "ner_tags": ner_tags,
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- }
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- guid += 1
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- tokens = []
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- ner_tags = []
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- else:
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- # tokens are tab separated
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- splits = line.split("\t")
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- tokens.append(splits[0])
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- ner_tags.append(splits[1].rstrip())
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- # last example
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- if tokens:
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- yield guid, {
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- "id": str(guid),
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- "tokens": tokens,
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- "ner_tags": ner_tags,
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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bc2gm_corpus/train-00000-of-00001.parquet ADDED
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bc2gm_corpus/validation-00000-of-00001.parquet ADDED
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