Update files from the datasets library (from 1.2.0)

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

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README.md

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+---
+annotations_creators:
+- expert-generated
+- machine-generated
+language_creators:
+- found
+languages:
+- de
+licenses:
+- cc-by-sa-3-0
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+- text-scoring
+task_ids:
+- sentiment-scoring
+- structure-prediction-other-pos-tagging
+---
+
+# Dataset Card for SentiWS
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [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:** https://wortschatz.uni-leipzig.de/en/download
+- **Repository:** [Needs More Information]
+- **Paper:** http://www.lrec-conf.org/proceedings/lrec2010/pdf/490_Paper.pdf
+- **Leaderboard:** [Needs More Information]
+- **Point of Contact:** [Needs More Information]
+
+### Dataset Summary
+
+SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, opinion mining etc. It lists positive and negative polarity bearing words weighted within the interval of [-1; 1] plus their part of speech tag, and if applicable, their inflections. The current version of SentiWS contains around 1,650 positive and 1,800 negative words, which sum up to around 16,000 positive and 18,000 negative word forms incl. their inflections, respectively. It not only contains adjectives and adverbs explicitly expressing a sentiment, but also nouns and verbs implicitly containing one.
+
+### Supported Tasks and Leaderboards
+
+Sentiment-Scoring, Pos-Tagging
+
+### Languages
+
+German
+
+## Dataset Structure
+
+### Data Instances
+For pos-tagging:
+```
+{ 
+"word":"Abbau"
+"pos_tag": 0
+}
+```
+For sentiment-scoring:
+```
+{
+"word":"Abbau"
+"sentiment-score":-0.058
+}
+``` 
+
+### Data Fields
+
+SentiWS is UTF8-encoded text.
+For pos-tagging:
+- word: one word as a string,
+- pos_tag: the part-of-speech tag of the word as an integer,
+For sentiment-scoring:
+- word: one word as a string,
+- sentiment-score: the sentiment score of the word as a float between -1 and 1,
+
+The POS tags are ["NN", "VVINF", "ADJX", "ADV"] -> ["noun", "verb", "adjective", "adverb"], and positive and negative polarity bearing words are weighted within the interval of [-1, 1].
+
+### Data Splits
+
+ train: 1,650 negative and 1,818 positive words
+
+## Dataset Creation
+
+### Curation Rationale
+
+[Needs More Information]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[Needs More Information]
+
+#### Who are the source language producers?
+
+[Needs More Information]
+
+### Annotations
+
+#### Annotation process
+
+[Needs More Information]
+
+#### Who are the annotators?
+
+[Needs More Information]
+
+### Personal and Sensitive Information
+
+[Needs More Information]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Needs More Information]
+
+### Discussion of Biases
+
+[Needs More Information]
+
+### Other Known Limitations
+
+[Needs More Information]
+
+## Additional Information
+
+### Dataset Curators
+
+[Needs More Information]
+
+### Licensing Information
+
+Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License
+
+### Citation Information
+@INPROCEEDINGS{remquahey2010,
+title = {SentiWS -- a Publicly Available German-language Resource for Sentiment Analysis},
+booktitle = {Proceedings of the 7th International Language Resources and Evaluation (LREC'10)},
+author = {Remus, R. and Quasthoff, U. and Heyer, G.},
+year = {2010}
+}

dataset_infos.json

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+{"pos-tagging": {"description": "SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, and pos-tagging. The POS tags are [\"NN\", \"VVINF\", \"ADJX\", \"ADV\"] -> [\"noun\", \"verb\", \"adjective\", \"adverb\"], and positive and negative polarity bearing words are weighted within the interval of [-1, 1].\n", "citation": "@INPROCEEDINGS{remquahey2010,\ntitle = {SentiWS -- a Publicly Available German-language Resource for Sentiment Analysis},\nbooktitle = {Proceedings of the 7th International Language Resources and Evaluation (LREC'10)},\nauthor = {Remus, R. and Quasthoff, U. and Heyer, G.},\nyear = {2010}\n}\n", "homepage": "", "license": "Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License", "features": {"word": {"dtype": "string", "id": null, "_type": "Value"}, "pos-tag": {"num_classes": 4, "names": ["NN", "VVINF", "ADJX", "ADV"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "senti_ws", "config_name": "pos-tagging", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 75530, "num_examples": 3471, "dataset_name": "senti_ws"}}, "download_checksums": {"https://pcai056.informatik.uni-leipzig.de/downloads/etc/SentiWS/SentiWS_v2.0.zip": {"num_bytes": 97748, "checksum": "4dd6ce99a44b5122c04fe0e7ca36db1f94d738201095edabb0a16cc98f160b91"}}, "download_size": 97748, "post_processing_size": null, "dataset_size": 75530, "size_in_bytes": 173278}, "sentiment-scoring": {"description": "SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, and pos-tagging. The POS tags are [\"NN\", \"VVINF\", \"ADJX\", \"ADV\"] -> [\"noun\", \"verb\", \"adjective\", \"adverb\"], and positive and negative polarity bearing words are weighted within the interval of [-1, 1].\n", "citation": "@INPROCEEDINGS{remquahey2010,\ntitle = {SentiWS -- a Publicly Available German-language Resource for Sentiment Analysis},\nbooktitle = {Proceedings of the 7th International Language Resources and Evaluation (LREC'10)},\nauthor = {Remus, R. and Quasthoff, U. and Heyer, G.},\nyear = {2010}\n}\n", "homepage": "", "license": "Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License", "features": {"word": {"dtype": "string", "id": null, "_type": "Value"}, "sentiment-score": {"dtype": "float32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "senti_ws", "config_name": "sentiment-scoring", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 61646, "num_examples": 3471, "dataset_name": "senti_ws"}}, "download_checksums": {"https://pcai056.informatik.uni-leipzig.de/downloads/etc/SentiWS/SentiWS_v2.0.zip": {"num_bytes": 97748, "checksum": "4dd6ce99a44b5122c04fe0e7ca36db1f94d738201095edabb0a16cc98f160b91"}}, "download_size": 97748, "post_processing_size": null, "dataset_size": 61646, "size_in_bytes": 159394}}

dummy/pos-tagging/1.1.0/dummy_data.zip

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+size 1345

dummy/sentiment-scoring/1.1.0/dummy_data.zip

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+size 1345

senti_ws.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""SentiWS: German-language resource for sentiment analysis, pos-tagging"""
+
+from __future__ import absolute_import, division, print_function
+
+import os
+
+import datasets
+
+
+_CITATION = """\
+@INPROCEEDINGS{remquahey2010,
+title = {SentiWS -- a Publicly Available German-language Resource for Sentiment Analysis},
+booktitle = {Proceedings of the 7th International Language Resources and Evaluation (LREC'10)},
+author = {Remus, R. and Quasthoff, U. and Heyer, G.},
+year = {2010}
+}
+"""
+
+_DESCRIPTION = """\
+SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, and pos-tagging. The POS tags are ["NN", "VVINF", "ADJX", "ADV"] -> ["noun", "verb", "adjective", "adverb"], and positive and negative polarity bearing words are weighted within the interval of [-1, 1].
+"""
+
+_HOMEPAGE = ""
+
+_LICENSE = "Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License"
+
+_URLs = ["https://pcai056.informatik.uni-leipzig.de/downloads/etc/SentiWS/SentiWS_v2.0.zip"]
+
+
+class SentiWS(datasets.GeneratorBasedBuilder):
+    """SentiWS: German-language resource for sentiment analysis, pos-tagging"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="pos-tagging", version=VERSION, description="This covers pos-tagging task"),
+        datasets.BuilderConfig(
+            name="sentiment-scoring",
+            version=VERSION,
+            description="This covers the sentiment-scoring in [-1, 1] corresponding to (negative, positive) sentiment",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "pos-tagging"
+
+    def _info(self):
+
+        if (
+            self.config.name == "pos-tagging"
+        ):  # the pos-tags are ["NN", "VVINF", "ADJX", "ADV"] -> ["noun", "verb", "adjective", "adverb"]
+            features = datasets.Features(
+                {
+                    "word": datasets.Value("string"),
+                    "pos-tag": datasets.ClassLabel(names=["NN", "VVINF", "ADJX", "ADV"]),
+                }
+            )
+        else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
+            features = datasets.Features(
+                {
+                    "word": datasets.Value("string"),
+                    "sentiment-score": datasets.Value("float32"),
+                }
+            )
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        my_urls = _URLs
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "sourcefiles": [
+                        os.path.join(data_dir[0], f)
+                        for f in ["SentiWS_v2.0_Positive.txt", "SentiWS_v2.0_Negative.txt"]
+                    ],
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, sourcefiles, split):
+        """ Yields examples. """
+        # TODO: This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method.
+        # It is in charge of opening the given file and yielding (key, example) tuples from the dataset
+        # The key is not important, it's more here for legacy reason (legacy from tfds)
+        for filepath in sourcefiles:
+            with open(filepath, encoding="utf-8") as f:
+                for id_, row in enumerate(f):
+                    word = row.split("|")[0]
+                    if self.config.name == "pos-tagging":
+                        tag = row.split("|")[1].split("\t")[0]
+                        yield id_, {"word": word, "pos-tag": tag}
+                    else:
+                        sentiscore = row.split("|")[1].split("\t")[1]
+                        yield id_, {"word": word, "sentiment-score": float(sentiscore)}