Update files from the datasets library (from 1.18.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.18.0

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README.md

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+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+languages:
+- en
+licenses:
+- unknown
+multilinguality:
+- monolingual
+pretty_name: 'text2log'
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- machine-translation
+---
+
+# Dataset Card for text2log
+
+## 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:**
+- **Repository:** [GitHub](https://github.com/alevkov/text2log)
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:** https://github.com/alevkov
+
+### Dataset Summary
+
+The dataset contains 100,000 simple English sentences selected and filtered from `enTenTen15` and their translation into First Order Logic (FOL) using `ccg2lambda`.
+
+### Supported Tasks and Leaderboards
+
+'semantic-parsing': The data set is used to train models which can generate FOL statements from natural language text
+
+### Languages
+
+en-US
+
+## Dataset Structure
+
+### Data Instances
+
+```
+{
+'clean':'All things that are new are good.',
+'trans':'all x1.(_thing(x1) -> (_new(x1) -> _good(x1)))'
+}
+```
+
+### Data Fields
+
+- 'clean': a simple English sentence
+- 'trans': the corresponding translation into Lambda Dependency-based Compositional Semantics 
+
+### Data Splits
+
+No predefined train/test split is given. The authors used a 80/20 split
+
+## Dataset Creation
+
+### Curation Rationale
+
+The text2log data set is used to improve FOL statement generation from natural text
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+Short text samples selected from enTenTen15
+
+#### Who are the source language producers?
+
+See https://www.sketchengine.eu/ententen-english-corpus/
+
+### Annotations
+
+#### Annotation process
+
+Machine generated using https://github.com/mynlp/ccg2lambda
+
+#### Who are the annotators?
+
+none
+
+### Personal and Sensitive Information
+
+The dataset does not contain personal or sensitive 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
+
+None given
+
+### Citation Information
+```bibtex
+@INPROCEEDINGS{9401852, 
+author={Levkovskyi, Oleksii and Li, Wei},
+booktitle={SoutheastCon 2021},
+title={Generating Predicate Logic Expressions from Natural Language},
+year={2021},
+volume={},
+number={},
+pages={1-8},
+doi={10.1109/SoutheastCon45413.2021.9401852}
+}
+```
+
+### Contributions
+
+Thanks to [@apergo-ai](https://github.com/apergo-ai) for adding this dataset.

dataset_infos.json

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+{"default": {"description": "The dataset contains about 100,000 simple English sentences selected and filtered from enTenTen15 and their translation into First Order Logic (FOL) Lambda Dependency-based Compositional Semantics using ccg2lambda.\n", "citation": "@INPROCEEDINGS{9401852,  author={Levkovskyi, Oleksii and Li, Wei},  booktitle={SoutheastCon 2021},   title={Generating Predicate Logic Expressions from Natural Language},   year={2021},  volume={},  number={},  pages={1-8},  doi={10.1109/SoutheastCon45413.2021.9401852}}\n", "homepage": "https://github.com/alevkov/text2log", "license": "none provided", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "fol_translation": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "text2log", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10358134, "num_examples": 101931, "dataset_name": "text2log"}}, "download_checksums": {"https://raw.githubusercontent.com/apergo-ai/text2log/main/dat/text2log_clean.csv": {"num_bytes": 9746473, "checksum": "1cdfcd5ece1e95837880d552d910d132620b0b41afd25c0bf4d0a35966fb8fd8"}}, "download_size": 9746473, "post_processing_size": null, "dataset_size": 10358134, "size_in_bytes": 20104607}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:46129ad203decbf13151c8bc2fb87797e9a5b733064714a6b34b29c3ed1909d3
+size 408

text2log.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.
+
+"""The text2log dataset"""
+
+
+import csv
+
+import datasets
+
+
+_CITATION = """\
+@INPROCEEDINGS{9401852,  author={Levkovskyi, Oleksii and Li, Wei},  booktitle={SoutheastCon 2021},   title={Generating Predicate Logic Expressions from Natural Language},   year={2021},  volume={},  number={},  pages={1-8},  doi={10.1109/SoutheastCon45413.2021.9401852}}
+"""
+
+_DESCRIPTION = """\
+The dataset contains about 100,000 simple English sentences selected and filtered from enTenTen15 and their translation into First Order Logic (FOL) Lambda Dependency-based Compositional Semantics using ccg2lambda.
+"""
+
+_HOMEPAGE = "https://github.com/alevkov/text2log"
+
+_LICENSE = "none provided"
+
+
+_URLS = {
+    "csv": "https://raw.githubusercontent.com/apergo-ai/text2log/main/dat/text2log_clean.csv",
+    "zip": "https://raw.githubusercontent.com/apergo-ai/text2log/main/dat/text2log_clean.zip",
+}
+
+
+class Text2log(datasets.GeneratorBasedBuilder):
+    """Simple English sentences and FOL representations using LDbCS"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+
+        features = datasets.Features(
+            {
+                "sentence": datasets.Value("string"),
+                "fol_translation": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            supervised_keys=None,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        test_path = dl_manager.download_and_extract(_URLS["csv"])
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": test_path}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Generate text2log dataset examples."""
+        with open(filepath, encoding="utf-8") as csv_file:
+            csv_reader = csv.reader(
+                csv_file, quotechar='"', delimiter=";", quoting=csv.QUOTE_ALL, skipinitialspace=True
+            )
+            next(csv_reader)
+            for id_, row in enumerate(csv_reader):
+                yield id_, {
+                    "sentence": str(row[0]),
+                    "fol_translation": str(row[1]),
+                }