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:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# Dataset Card for [Dataset Name]
+
+## 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:** [linnaeus](http://linnaeus.sourceforge.net/)
+- **Repository:**
+- **Paper:** [BMC Bioinformatics](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-85)
+- **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 species mentioned, `1` signals the first token of a species and `2` the subsequent tokens of the species.  
+
+### 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]

dataset_infos.json

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+{"linnaeus": {"description": "A novel corpus of full-text documents manually annotated for species mentions.\n", "citation": "@article{gerner2010linnaeus,\n         title={LINNAEUS: a species name identification system for biomedical literature},\n         author={Gerner, Martin and Nenadic, Goran and Bergman, Casey M},\n         journal={BMC bioinformatics},\n         volume={11},\n         number={1},\n         pages={85},\n         year={2010},\n         publisher={Springer}\n}\n", "homepage": "http://linnaeus.sourceforge.net/", "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", "I"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "linnaeus", "config_name": "linnaeus", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4772417, "num_examples": 11936, "dataset_name": "linnaeus"}, "validation": {"name": "validation", "num_bytes": 1592823, "num_examples": 4079, "dataset_name": "linnaeus"}, "test": {"name": "test", "num_bytes": 2802877, "num_examples": 7143, "dataset_name": "linnaeus"}}, "download_checksums": {"https://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/": {"num_bytes": 18204624, "checksum": "30522c752fd90e6da05f117a52da13174b246e4980e46840e6e1737dc67e1d27"}}, "download_size": 18204624, "post_processing_size": null, "dataset_size": 9168117, "size_in_bytes": 27372741}}

dummy/linnaeus/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d63b26856cc74dbb464ea22d709946e67caff7291bbeec323f6368518d73f7e2
+size 12082

linnaeus.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
+"""LINNAEUS: A species name identification system for biomedical literature"""
+
+import logging
+import os
+
+import datasets
+
+
+_CITATION = """\
+@article{gerner2010linnaeus,
+         title={LINNAEUS: a species name identification system for biomedical literature},
+         author={Gerner, Martin and Nenadic, Goran and Bergman, Casey M},
+         journal={BMC bioinformatics},
+         volume={11},
+         number={1},
+         pages={85},
+         year={2010},
+         publisher={Springer}
+}
+"""
+
+_DESCRIPTION = """\
+A novel corpus of full-text documents manually annotated for species mentions.
+"""
+
+_HOMEPAGE = "http://linnaeus.sourceforge.net/"
+_URL = "https://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/"
+_BIOBERT_NER_DATASET_DIRECTORY = "linnaeus"
+_TRAINING_FILE = "train.tsv"
+_DEV_FILE = "devel.tsv"
+_TEST_FILE = "test.tsv"
+
+
+class LinnaeusConfig(datasets.BuilderConfig):
+    """BuilderConfig for Linnaeus"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Linnaeus.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(LinnaeusConfig, self).__init__(**kwargs)
+
+
+class Linnaeus(datasets.GeneratorBasedBuilder):
+    """Linnaeus dataset."""
+
+    BUILDER_CONFIGS = [
+        LinnaeusConfig(name="linnaeus", version=datasets.Version("1.0.0"), description="Linnaeus dataset"),
+    ]
+
+    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",
+                                "I",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "biobert_ner_datasets": _URL,
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+        dataset_directory = os.path.join(downloaded_files["biobert_ner_datasets"], _BIOBERT_NER_DATASET_DIRECTORY)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dataset_directory, _TRAINING_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(dataset_directory, _DEV_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dataset_directory, _TEST_FILE)}
+            ),
+        ]
+
+    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,
+            }