Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+languages:
+- en
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# Dataset Card for bc2gm_corpus
+
+## Table of Contents
+- [Dataset Card for [Dataset Name]](#dataset-card-for-dataset-name)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [Github](https://github.com/spyysalo/bc2gm-corpus/)
+- **Repository:** [Github](https://github.com/spyysalo/bc2gm-corpus/)
+- **Paper:** [NCBI](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/)
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+- `id`: Sentence identifier.  
+- `tokens`: Array of tokens composing a sentence.  
+- `ner_tags`: Array of tags, where `0` indicates no disease mentioned, `1` signals the first token of a disease and `2` the subsequent disease tokens.  
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

bc2gm_corpus.py

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+# 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
+"""BioCreative II gene mention recognition Corpus"""
+
+import logging
+
+import datasets
+
+
+_CITATION = """\
+@article{smith2008overview,
+        title={Overview of BioCreative II gene mention recognition},
+        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},
+        journal={Genome biology},
+        volume={9},
+        number={S2},
+        pages={S2},
+        year={2008},
+        publisher={Springer}
+}
+"""
+
+_DESCRIPTION = """\
+Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop.
+In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions.
+A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721.
+Here we present brief descriptions of all the methods used and a statistical analysis of the results.
+We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible,
+and furthermore that the best result makes use of the lowest scoring submissions.
+
+For more details, see: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/
+
+The original dataset can be downloaded from: https://biocreative.bioinformatics.udel.edu/resources/corpora/biocreative-ii-corpus/
+This dataset has been converted to CoNLL format for NER using the following tool: https://github.com/spyysalo/standoff2conll
+"""
+
+_HOMEPAGE = "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/"
+_URL = "https://github.com/spyysalo/bc2gm-corpus/raw/master/conll/"
+_TRAINING_FILE = "train.tsv"
+_DEV_FILE = "devel.tsv"
+_TEST_FILE = "test.tsv"
+
+
+class Bc2gmCorpusConfig(datasets.BuilderConfig):
+    """BuilderConfig for Bc2gmCorpus"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Bc2gmCorpus.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(Bc2gmCorpusConfig, self).__init__(**kwargs)
+
+
+class Bc2gmCorpus(datasets.GeneratorBasedBuilder):
+    """Bc2gmCorpus dataset."""
+
+    BUILDER_CONFIGS = [
+        Bc2gmCorpusConfig(name="bc2gm_corpus", version=datasets.Version("1.0.0"), description="bc2gm corpus"),
+    ]
+
+    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-GENE",
+                                "I-GENE",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAINING_FILE}",
+            "dev": f"{_URL}{_DEV_FILE}",
+            "test": f"{_URL}{_TEST_FILE}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            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:
+                    # tokens are tab separated
+                    splits = line.split("\t")
+                    tokens.append(splits[0])
+                    ner_tags.append(splits[1].rstrip())
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "tokens": tokens,
+                "ner_tags": ner_tags,
+            }

dataset_infos.json

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+{"bc2gm_corpus": {"description": "Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. \nIn this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. \nA variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. \nHere we present brief descriptions of all the methods used and a statistical analysis of the results. \nWe also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, \nand furthermore that the best result makes use of the lowest scoring submissions.\n\nFor more details, see: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/\n\nThe original dataset can be downloaded from: https://biocreative.bioinformatics.udel.edu/resources/corpora/biocreative-ii-corpus/\nThis dataset has been converted to CoNLL format for NER using the following tool: https://github.com/spyysalo/standoff2conll\n", "citation": "@article{smith2008overview,\n        title={Overview of BioCreative II gene mention recognition},\n        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},\n        journal={Genome biology},\n        volume={9},\n        number={S2},\n        pages={S2},\n        year={2008},\n        publisher={Springer}\n}\n", "homepage": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 3, "names": ["O", "B-GENE", "I-GENE"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "bc2gm_corpus", "config_name": "bc2gm_corpus", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 6095172, "num_examples": 12501, "dataset_name": "bc2gm_corpus"}, "validation": {"name": "validation", "num_bytes": 1215951, "num_examples": 2501, "dataset_name": "bc2gm_corpus"}, "test": {"name": "test", "num_bytes": 2454621, "num_examples": 5001, "dataset_name": "bc2gm_corpus"}}, "download_checksums": {"https://github.com/spyysalo/bc2gm-corpus/raw/master/conll/train.tsv": {"num_bytes": 2894093, "checksum": "07f696560252dc5a3d47a5cea1ce36b7434865131b5bc4b3a6d1fb02a382ce10"}, "https://github.com/spyysalo/bc2gm-corpus/raw/master/conll/devel.tsv": {"num_bytes": 577641, "checksum": "639fe423c00beeb33e83ef71e90af765c6d9cde61f52df0fbbb9d624302f5437"}, "https://github.com/spyysalo/bc2gm-corpus/raw/master/conll/test.tsv": {"num_bytes": 1165019, "checksum": "ac7745e40d97ffdf603aae661da37fa6065a7e2f9067ea1f47bfae3e5bf5d583"}}, "download_size": 4636753, "post_processing_size": null, "dataset_size": 9765744, "size_in_bytes": 14402497}}

dummy/bc2gm_corpus/1.0.0/dummy_data.zip

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+size 600