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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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
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+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+  - expert-generated
+language_creators:
+  - other
+languages:
+  - ko
+licenses:
+  - mit
+multilinguality:
+  - monolingual
+size_categories:
+  - 1K<n<10K
+source_datasets:
+  - original
+task_categories:
+  - structure-prediction
+task_ids:
+  - named-entity-recognition
+---
+
+# Dataset Card for [Dataset Name]
+
+## 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:** [Github](https://github.com/kmounlp/NER)
+- **Repository:** [Github](https://github.com/kmounlp/NER)
+- **Paper:**
+- **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
+
+Each row consists of the following fields:
+
+- `text`: The full text, as is
+- `annot_text`: Annotated text including POS-tagged information
+- `tokens`: An ordered list of tokens from the full text
+- `pos_tags`: Part-of-speech tags for each token
+- `ner_tags`: Named entity recognition tags for each token
+
+Note that by design, the length of `tokens`, `pos_tags`, and `ner_tags` will always be identical.
+
+`pos_tags` corresponds to the list below:
+
+```
+['SO', 'SS', 'VV', 'XR', 'VCP', 'JC', 'VCN', 'JKB', 'MM', 'SP', 'XSN', 'SL', 'NNP', 'NP', 'EP', 'JKQ', 'IC', 'XSA', 'EC', 'EF', 'SE', 'XPN', 'ETN', 'SH', 'XSV', 'MAG', 'SW', 'ETM', 'JKO', 'NNB', 'MAJ', 'NNG', 'JKV', 'JKC', 'VA', 'NR', 'JKG', 'VX', 'SF', 'JX', 'JKS', 'SN']
+```
+
+`ner_tags` correspond to the following:
+
+```
+["I", "O", "B_OG", "B_TI", "B_LC", "B_DT", "B_PS"]
+```
+
+The prefix `B` denotes the first item of a phrase, and an `I` denotes any non-initial word. In addition, `OG` represens an organization; `TI`, time; `DT`, date, and `PS`, person.
+
+### 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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+{"default": {"description": "Korean named entity recognition dataset\n", "citation": "@InProceedings{Kim:2016,\n  title     = \"Korean Named Entity Recognition Dataset\",\n  authors   = \"Jae-Hoon Kim\",\n  publisher = \"GitHub\",\n  year      = \"2016\"\n}\n", "homepage": "https://github.com/kmounlp/NER", "license": "NER License, MIT License for non-commercial use", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "annot_text": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pos_tags": {"feature": {"num_classes": 42, "names": ["SO", "SS", "VV", "XR", "VCP", "JC", "VCN", "JKB", "MM", "SP", "XSN", "SL", "NNP", "NP", "EP", "JKQ", "IC", "XSA", "EC", "EF", "SE", "XPN", "ETN", "SH", "XSV", "MAG", "SW", "ETM", "JKO", "NNB", "MAJ", "NNG", "JKV", "JKC", "VA", "NR", "JKG", "VX", "SF", "JX", "JKS", "SN"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 7, "names": ["I", "O", "B_OG", "B_TI", "B_LC", "B_DT", "B_PS"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "kor_ner", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3948938, "num_examples": 2928, "dataset_name": "kor_ner"}, "test": {"name": "test", "num_bytes": 476850, "num_examples": 366, "dataset_name": "kor_ner"}, "validation": {"name": "validation", "num_bytes": 486178, "num_examples": 366, "dataset_name": "kor_ner"}}, "download_checksums": {"https://raw.githubusercontent.com/kmounlp/NER/master/2016klp/ner.train": {"num_bytes": 2808804, "checksum": "ae8d0b9ecc49a36ec8fd30ebed5accf2e4da23e8e432d0e4e494be049412c1cf"}, "https://raw.githubusercontent.com/kmounlp/NER/master/2016klp/ner.test": {"num_bytes": 338858, "checksum": "35396b5d88d9c3feb74a5e43097482e4379ff522bc66ed0d2a1e40a4e34a5645"}, "https://raw.githubusercontent.com/kmounlp/NER/master/2016klp/ner.dev": {"num_bytes": 345513, "checksum": "0b6afc8e02a5bb3439b697da7aa6bc274b1128f84c14f6bde85c7d0934b145d6"}}, "download_size": 3493175, "post_processing_size": null, "dataset_size": 4911966, "size_in_bytes": 8405141}}

dummy/1.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5b0703c3de2f56a96b7c0f6af11758194df0756648c126390918a2e71f77462e
+size 3357

kor_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.
+"""Korean named entity recognition dataset"""
+
+from __future__ import absolute_import, division, print_function
+
+import logging
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{Kim:2016,
+  title     = "Korean Named Entity Recognition Dataset",
+  authors   = "Jae-Hoon Kim",
+  publisher = "GitHub",
+  year      = "2016"
+}
+"""
+
+
+_DESCRIPTION = """\
+Korean named entity recognition dataset
+"""
+
+_HOMEPAGE = "https://github.com/kmounlp/NER"
+
+_LICENSE = "NER License, MIT License for non-commercial use"
+
+_URL = "https://raw.githubusercontent.com/kmounlp/NER/master/2016klp/ner."
+_URLs = {key: _URL + key for key in ("train", "test", "dev")}
+
+
+class KorNER(datasets.GeneratorBasedBuilder):
+    """Korean Named entity recognition dataset"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "annot_text": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "SO",
+                                "SS",
+                                "VV",
+                                "XR",
+                                "VCP",
+                                "JC",
+                                "VCN",
+                                "JKB",
+                                "MM",
+                                "SP",
+                                "XSN",
+                                "SL",
+                                "NNP",
+                                "NP",
+                                "EP",
+                                "JKQ",
+                                "IC",
+                                "XSA",
+                                "EC",
+                                "EF",
+                                "SE",
+                                "XPN",
+                                "ETN",
+                                "SH",
+                                "XSV",
+                                "MAG",
+                                "SW",
+                                "ETM",
+                                "JKO",
+                                "NNB",
+                                "MAJ",
+                                "NNG",
+                                "JKV",
+                                "JKC",
+                                "VA",
+                                "NR",
+                                "JKG",
+                                "VX",
+                                "SF",
+                                "JX",
+                                "JKS",
+                                "SN",
+                            ]
+                        )
+                    ),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(names=["I", "O", "B_OG", "B_TI", "B_LC", "B_DT", "B_PS"])
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": downloaded_files["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": downloaded_files["test"],
+                    "split": "test",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": downloaded_files["dev"],
+                    "split": "validation",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            text = ""
+            annot_text = ""
+            tokens = []
+            pos_tags = []
+            ner_tags = []
+            for id_, row in enumerate(f):
+                row = row.strip()
+                if not row:
+                    yield id_, {
+                        "text": text,
+                        "annot_text": annot_text,
+                        "tokens": tokens,
+                        "pos_tags": pos_tags,
+                        "ner_tags": ner_tags,
+                    }
+                    tokens.clear()
+                    pos_tags.clear()
+                    ner_tags.clear()
+                    continue
+                if row[0] == ";":
+                    text = row[2:]
+                elif row[0] == "$":
+                    annot_text = row[1:]
+                else:
+                    _, token, pos_tag, ner_tag = row.split("\t")
+                    tokens.append(token)
+                    pos_tags.append(pos_tag)
+                    ner_tags.append(ner_tag)