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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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- ig
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# Dataset Card for Igbo NER dataset
+
+## 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-fields)
+  - [Data Splits](#data-splits)
+- [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://github.com/IgnatiusEzeani/IGBONLP/tree/master/ig_ner
+- **Repository:** https://github.com/IgnatiusEzeani/IGBONLP/tree/master/ig_ner
+- **Paper:** https://arxiv.org/abs/2004.00648
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+Here is an example from the dataset:
+```
+{'content_n': 'content_0', 'named_entity': 'Ike Ekweremmadụ', 'sentences': ['Ike Ekweremmadụ', "Ike ịda jụụ otụ nkeji banyere oke ogbugbu na-eme n'ala Naijiria agwụla Ekweremmadụ"]}
+```
+
+### Data Fields
+
+- content_n : ID 
+- named_entity : Name of the entity 
+- sentences : List of sentences for the entity 
+
+### 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
+
+@misc{ezeani2020igboenglish,  
+    title={Igbo-English Machine Translation: An Evaluation Benchmark},  
+    author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},  
+    year={2020},  
+    eprint={2004.00648},  
+    archivePrefix={arXiv},  
+    primaryClass={cs.CL}   
+}

dataset_infos.json

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+{"ner_data": {"description": "Igbo Named Entity Recognition Dataset\n", "citation": "@misc{ezeani2020igboenglish,\n    title={Igbo-English Machine Translation: An Evaluation Benchmark},\n    author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},\n    year={2020},\n    eprint={2004.00648},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/IgnatiusEzeani/IGBONLP/tree/master/ig_ner", "license": "", "features": {"content_n": {"dtype": "string", "id": null, "_type": "Value"}, "named_entity": {"dtype": "string", "id": null, "_type": "Value"}, "sentences": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "igbo_ner", "config_name": "ner_data", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 60315228, "num_examples": 30715, "dataset_name": "igbo_ner"}}, "download_checksums": {"https://raw.githubusercontent.com/IgnatiusEzeani/IGBONLP/master/ig_ner/igbo_data.txt": {"num_bytes": 3311204, "checksum": "788141de3c325937d478ad4c960e759816dd324670333aed370916a06d8262eb"}}, "download_size": 3311204, "post_processing_size": null, "dataset_size": 60315228, "size_in_bytes": 63626432}, "free_text": {"description": "Igbo Named Entity Recognition Dataset\n", "citation": "@misc{ezeani2020igboenglish,\n    title={Igbo-English Machine Translation: An Evaluation Benchmark},\n    author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},\n    year={2020},\n    eprint={2004.00648},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/IgnatiusEzeani/IGBONLP/tree/master/ig_ner", "license": "", "features": {"sentences": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "igbo_ner", "config_name": "free_text", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1172152, "num_examples": 10000, "dataset_name": "igbo_ner"}}, "download_checksums": {"https://raw.githubusercontent.com/IgnatiusEzeani/IGBONLP/master/ig_ner/igbo_data10000.txt": {"num_bytes": 1132151, "checksum": "6f664460a5beb3928063463041bde5a8b31fe4ac02d96f77094ef099a8e4f5c2"}}, "download_size": 1132151, "post_processing_size": null, "dataset_size": 1172152, "size_in_bytes": 2304303}}

dummy/free_text/1.1.0/dummy_data.zip

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dummy/ner_data/1.1.0/dummy_data.zip

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igbo_ner.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.
+"""Igbo Named Entity Recognition Dataset"""
+
+from __future__ import absolute_import, division, print_function
+
+import datasets
+
+
+_CITATION = """\
+@misc{ezeani2020igboenglish,
+    title={Igbo-English Machine Translation: An Evaluation Benchmark},
+    author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},
+    year={2020},
+    eprint={2004.00648},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+Igbo Named Entity Recognition Dataset
+"""
+
+_HOMEPAGE = "https://github.com/IgnatiusEzeani/IGBONLP/tree/master/ig_ner"
+
+_URLs = {
+    "ner_data": "https://raw.githubusercontent.com/IgnatiusEzeani/IGBONLP/master/ig_ner/igbo_data.txt",
+    "free_text": "https://raw.githubusercontent.com/IgnatiusEzeani/IGBONLP/master/ig_ner/igbo_data10000.txt",
+}
+
+
+class IgboNer(datasets.GeneratorBasedBuilder):
+    """Dataset from the Igbo NER Project"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="ner_data",
+            version=VERSION,
+            description="This dataset contains the named entity and all the sentences containing that entity.",
+        ),
+        datasets.BuilderConfig(
+            name="free_text", version=VERSION, description="This dataset contains all sentences used for NER."
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "ner_data"
+
+    def _info(self):
+        if self.config.name == "ner_data":
+            features = datasets.Features(
+                {
+                    "content_n": datasets.Value("string"),
+                    "named_entity": datasets.Value("string"),
+                    "sentences": datasets.Sequence(datasets.Value("string")),
+                }
+            )
+        else:
+            features = datasets.Features(
+                {
+                    "sentences": datasets.Value("string"),
+                }
+            )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        my_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir,
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """ Yields examples. """
+        dictionary = {}
+        with open(filepath, "r", encoding="utf-8-sig") as f:
+            if self.config.name == "ner_data":
+                for id_, row in enumerate(f):
+                    row = row.strip().split("\t")
+                    content_n = row[0]
+                    if content_n in dictionary.keys():
+                        (dictionary[content_n]["sentences"]).append(row[1])
+                    else:
+                        dictionary[content_n] = {}
+                        dictionary[content_n]["named_entity"] = row[1]
+                        dictionary[content_n]["sentences"] = [row[1]]
+                    yield id_, {
+                        "content_n": content_n,
+                        "named_entity": dictionary[content_n]["named_entity"],
+                        "sentences": dictionary[content_n]["sentences"],
+                    }
+            else:
+                for id_, row in enumerate(f):
+                    yield id_, {
+                        "sentences": row.strip(),
+                    }